MIREX Wiki - User contributions [en]

2020:Automatic Lyrics-to-Audio Alignment Results

2020-10-17T00:48:01Z

Yun Hao: /* Per-track results */

= General Legend =

{| border="1" cellspacing="0" style="text-align: left; width: 800px;"
|- style="background: yellow"
! width="80" | Sub code
! width="200" | Submission name
! width="80" style="text-align: center;" | Abstract
! width="540" | Contributors
|-

! GGL1
| NUS || style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2020/GL1.pdf PDF] || [https://www.comp.nus.edu.sg/~chitrale/ Chitralekha Gupta], [http://ece.nus.edu.sg/drupal/?q=node/159 Haizhou Li]
|-

! GGL2
| NUS || style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2020/GL1.pdf PDF] || [https://www.comp.nus.edu.sg/~chitrale/ Chitralekha Gupta], [http://ece.nus.edu.sg/drupal/?q=node/159 Haizhou Li]
|-

! ZWZL1
| ZWZL1 || style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2020/ZWZL1.pdf PDF] || [], [], []
|-

! ZWZL2
| ZWZL2 || style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2020/ZWZL1.pdf PDF] || [], [], []
|-

! ZWZL3
| ZWZL3 || style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2020/ZWZL1.pdf PDF] || [], [], []
|-

! DDA1
| Audio2Lyrics_emirdemirel || style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2020/DDA3.pdf PDF] || [http://www.eecs.qmul.ac.uk/profiles/demirelemir.html Emir Demirel]
|-

! CC1
| Mir lab || style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2020/CC1.pdf PDF] || [Chun-Hao]
|-
|}

=Results=
UNDER CONSTRUCTION...

===Hansen's dataset a cappella===
====Summary Results====
<csv>2020/ala/HansensDataset_acappella/summary_HansensDataset_acappella.csv</csv>

====Per-track results====

GGL1
<csv>2020/ala/HansensDataset/GGL1/results.csv</csv>

GGL2
<csv>2020/ala/HansensDataset/GGL2/results.csv</csv>

ZWZL1
<csv>2020/ala/HansensDataset/ZWZL1/results.csv</csv>

ZWZL2
<csv>2020/ala/HansensDataset/ZWZL2/results.csv</csv>

ZWZL3
<csv>2020/ala/HansensDataset/ZWZL3/results.csv</csv>

DDA1
<csv>2020/ala/HansensDataset/DDA1/results.csv</csv>

===Hansen's dataset===
====Summary Results====
<csv>2020/ala/HansensDataset/summary_HansensDataset.csv</csv>

====Per-track results====

GGL1
<csv>2020/ala/HansensDataset/GGL1/results.csv</csv>

GGL2
<csv>2020/ala/HansensDataset/GGL2/results.csv</csv>

ZWZL1
<csv>2020/ala/HansensDataset/ZWZL1/results.csv</csv>

ZWZL2
<csv>2020/ala/HansensDataset/ZWZL2/results.csv</csv>

ZWZL3
<csv>2020/ala/HansensDataset/ZWZL3/results.csv</csv>

DDA1
<csv>2020/ala/HansensDataset/DDA1/results.csv</csv>

===Mauch's dataset===

====Summary Results====
<csv>2020/ala/MauchsDataset/summary_MauchsDataset.csv</csv>

====Per-track results====
GGL1
<csv>2020/ala/MauchsDataset/GGL1/results.csv</csv>

GGL2
<csv>2020/ala/MauchsDataset/GGL2/results.csv</csv>

ZWZL1
<csv>2020/ala/MauchsDataset/ZWZL1/results.csv</csv>

ZWZL2
<csv>2020/ala/MauchsDataset/ZWZL2/results.csv</csv>

ZWZL3
<csv>2020/ala/MauchsDataset/ZWZL3/results.csv</csv>

DDA1
<csv>2020/ala/MauchsDataset/DDA1/results.csv</csv>

===Jamendo dataset===

====Summary Results====
<csv>2020/ala/jamendolyrics/summary_jamendolyrics.csv</csv>

====Per-track results====

GGL1
<csv>2020/ala/jamendolyrics/GGL1/results.csv</csv>

GGL2
<csv>2020/ala/jamendolyrics/GGL2/results.csv</csv>

ZWZL1
<csv>2020/ala/jamendolyrics/ZWZL1/results.csv</csv>

ZWZL2
<csv>2020/ala/jamendolyrics/ZWZL2/results.csv</csv>

ZWZL3
<csv>2020/ala/jamendolyrics/ZWZL3/results.csv</csv>

DDA1
<csv>2020/ala/jamendolyrics/DDA1/results.csv</csv>

2020:Automatic Lyrics-to-Audio Alignment Results

2020-10-17T00:47:37Z

Yun Hao:

= General Legend =

{| border="1" cellspacing="0" style="text-align: left; width: 800px;"
|- style="background: yellow"
! width="80" | Sub code
! width="200" | Submission name
! width="80" style="text-align: center;" | Abstract
! width="540" | Contributors
|-

! GGL1
| NUS || style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2020/GL1.pdf PDF] || [https://www.comp.nus.edu.sg/~chitrale/ Chitralekha Gupta], [http://ece.nus.edu.sg/drupal/?q=node/159 Haizhou Li]
|-

! GGL2
| NUS || style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2020/GL1.pdf PDF] || [https://www.comp.nus.edu.sg/~chitrale/ Chitralekha Gupta], [http://ece.nus.edu.sg/drupal/?q=node/159 Haizhou Li]
|-

! ZWZL1
| ZWZL1 || style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2020/ZWZL1.pdf PDF] || [], [], []
|-

! ZWZL2
| ZWZL2 || style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2020/ZWZL1.pdf PDF] || [], [], []
|-

! ZWZL3
| ZWZL3 || style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2020/ZWZL1.pdf PDF] || [], [], []
|-

! DDA1
| Audio2Lyrics_emirdemirel || style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2020/DDA3.pdf PDF] || [http://www.eecs.qmul.ac.uk/profiles/demirelemir.html Emir Demirel]
|-

! CC1
| Mir lab || style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2020/CC1.pdf PDF] || [Chun-Hao]
|-
|}

=Results=
UNDER CONSTRUCTION...

===Hansen's dataset a cappella===
====Summary Results====
<csv>2020/ala/HansensDataset_acappella/summary_HansensDataset_acappella.csv</csv>

====Per-track results====

GGL1
<csv>2020/ala/HansensDataset/GGL1/results.csv</csv>

GGL2
<csv>2020/ala/HansensDataset/GGL2/results.csv</csv>

ZWZL1
<csv>2020/ala/HansensDataset/ZWZL1/results.csv</csv>

ZWZL2
<csv>2020/ala/HansensDataset/ZWZL2/results.csv</csv>

ZWZL3
<csv>2020/ala/HansensDataset/ZWZL3/results.csv</csv>

DDA1
<csv>2020/ala/HansensDataset/DDA1/results.csv</csv>

===Hansen's dataset===
====Summary Results====
<csv>2020/ala/HansensDataset/summary_HansensDataset.csv</csv>

====Per-track results====

GGL1
<csv>2020/ala/HansensDataset/GGL1/results.csv</csv>

GGL2
<csv>2020/ala/HansensDataset/GGL2/results.csv</csv>

ZWZL1
<csv>2020/ala/HansensDataset/ZWZL1/results.csv</csv>

ZWZL2
<csv>2020/ala/HansensDataset/ZWZL2/results.csv</csv>

ZWZL3
<csv>2020/ala/HansensDataset/ZWZL3/results.csv</csv>

DDA1
<csv>2020/ala/HansensDataset/DDA1/results.csv</csv>

===Mauch's dataset===

====Summary Results====
<csv>2020/ala/MauchsDataset/summary_MauchsDataset.csv</csv>

====Per-track results====
GGL1
<csv>2020/ala/MauchsDataset/GGL1/results.csv</csv>

GGL2
<csv>2020/ala/MauchsDataset/GGL2/results.csv</csv>

ZWZL1
<csv>2020/ala/MauchsDataset/ZWZL1/results.csv</csv>

ZWZL2
<csv>2020/ala/MauchsDataset/ZWZL2/results.csv</csv>

ZWZL3
<csv>2020/ala/MauchsDataset/ZWZL3/results.csv</csv>

DDA1
<csv>2020/ala/MauchsDataset/DDA1/results.csv</csv>

===Jamendo dataset===

====Summary Results====
<csv>2020/ala/jamendolyrics/summary_jamendolyrics.csv</csv>

====Per-track results====

GGL1
<csv>2020/ala/jamendolyrics/GGL1/metrics/results.csv</csv>

GGL2
<csv>2020/ala/jamendolyrics/GGL2/metrics/results.csv</csv>

ZWZL1
<csv>2020/ala/jamendolyrics/ZWZL1/metrics/results.csv</csv>

ZWZL2
<csv>2020/ala/jamendolyrics/ZWZL2/metrics/results.csv</csv>

ZWZL3
<csv>2020/ala/jamendolyrics/ZWZL3/metrics/results.csv</csv>

DDA1
<csv>2020/ala/jamendolyrics/DDA1/metrics/results.csv</csv>

2020:Automatic Lyrics-to-Audio Alignment Results

2020-10-17T00:40:48Z

Yun Hao: Reverted edits by Yun Hao (talk) to last revision by Georgi Dzhambazov

= General Legend =

{| border="1" cellspacing="0" style="text-align: left; width: 800px;"
|- style="background: yellow"
! width="80" | Sub code
! width="200" | Submission name
! width="80" style="text-align: center;" | Abstract
! width="540" | Contributors
|-

! GGL1
| NUS || style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2020/GL1.pdf PDF] || [https://www.comp.nus.edu.sg/~chitrale/ Chitralekha Gupta], [http://ece.nus.edu.sg/drupal/?q=node/159 Haizhou Li]
|-

! GGL2
| NUS || style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2020/GL1.pdf PDF] || [https://www.comp.nus.edu.sg/~chitrale/ Chitralekha Gupta], [http://ece.nus.edu.sg/drupal/?q=node/159 Haizhou Li]
|-

! ZWZL1
| ZWZL1 || style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2020/ZWZL1.pdf PDF] || [], [], []
|-

! ZWZL2
| ZWZL2 || style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2020/ZWZL1.pdf PDF] || [], [], []
|-

! ZWZL3
| ZWZL3 || style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2020/ZWZL1.pdf PDF] || [], [], []
|-

! DDA1
| Audio2Lyrics_emirdemirel || style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2020/DDA3.pdf PDF] || [http://www.eecs.qmul.ac.uk/profiles/demirelemir.html Emir Demirel]
|-

! CC1
| Mir lab || style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2020/CC1.pdf PDF] || [Chun-Hao]
|-
|}

=Results=
UNDER CONSTRUCTION...

===Hansen's dataset a cappella===
====Summary Results====
<csv>2020/ala/HansensDataset_acappella/summary_HansensDataset_acappella.csv</csv>

====Per-track results====

GGL1
<csv>2020/ala/HansensDataset/GGL1/metrics/results.csv</csv>

GGL2
<csv>2020/ala/HansensDataset/GGL2/metrics/results.csv</csv>

ZWZL1
<csv>2020/ala/HansensDataset/ZWZL1/metrics/results.csv</csv>

ZWZL2
<csv>2020/ala/HansensDataset/ZWZL2/metrics/results.csv</csv>

ZWZL3
<csv>2020/ala/HansensDataset/ZWZL3/metrics/results.csv</csv>

DDA1
<csv>2020/ala/HansensDataset/DDA1/metrics/results.csv</csv>

===Hansen's dataset===
====Summary Results====
<csv>2020/ala/HansensDataset/summary_HansensDataset.csv</csv>

====Per-track results====

GGL1
<csv>2020/ala/HansensDataset/GGL1/metrics/results.csv</csv>

GGL2
<csv>2020/ala/HansensDataset/GGL2/metrics/results.csv</csv>

ZWZL1
<csv>2020/ala/HansensDataset/ZWZL1/metrics/results.csv</csv>

ZWZL2
<csv>2020/ala/HansensDataset/ZWZL2/metrics/results.csv</csv>

ZWZL3
<csv>2020/ala/HansensDataset/ZWZL3/metrics/results.csv</csv>

DDA1
<csv>2020/ala/HansensDataset/DDA1/metrics/results.csv</csv>

===Mauch's dataset===

====Summary Results====
<csv>2020/ala/MauchsDataset/summary_MauchsDataset.csv</csv>

====Per-track results====
GGL1
<csv>2020/ala/MauchsDataset/GGL1/metrics/results.csv</csv>

GGL2
<csv>2020/ala/MauchsDataset/GGL2/metrics/results.csv</csv>

ZWZL1
<csv>2020/ala/MauchsDataset/ZWZL1/metrics/results.csv</csv>

ZWZL2
<csv>2020/ala/MauchsDataset/ZWZL2/metrics/results.csv</csv>

ZWZL3
<csv>2020/ala/MauchsDataset/ZWZL3/metrics/results.csv</csv>

DDA1
<csv>2020/ala/MauchsDataset/DDA1/metrics/results.csv</csv>

===Jamendo dataset===

====Summary Results====
<csv>2020/ala/jamendolyrics/summary_jamendolyrics.csv</csv>

====Per-track results====

GGL1
<csv>2020/ala/jamendolyrics/GGL1/metrics/results.csv</csv>

GGL2
<csv>2020/ala/jamendolyrics/GGL2/metrics/results.csv</csv>

ZWZL1
<csv>2020/ala/jamendolyrics/ZWZL1/metrics/results.csv</csv>

ZWZL2
<csv>2020/ala/jamendolyrics/ZWZL2/metrics/results.csv</csv>

ZWZL3
<csv>2020/ala/jamendolyrics/ZWZL3/metrics/results.csv</csv>

DDA1
<csv>2020/ala/jamendolyrics/DDA1/metrics/results.csv</csv>

2020:Automatic Lyrics-to-Audio Alignment Results

2020-10-17T00:39:21Z

Yun Hao: /* Per-track results */

2020:Automatic Lyrics-to-Audio Alignment Results

2020-10-17T00:38:58Z

Yun Hao: /* Per-track results */

= General Legend =

{| border="1" cellspacing="0" style="text-align: left; width: 800px;"
|- style="background: yellow"
! width="80" | Sub code
! width="200" | Submission name
! width="80" style="text-align: center;" | Abstract
! width="540" | Contributors
|-

! GGL1
| NUS || style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2020/GL1.pdf PDF] || [https://www.comp.nus.edu.sg/~chitrale/ Chitralekha Gupta], [http://ece.nus.edu.sg/drupal/?q=node/159 Haizhou Li]
|-

! GGL2
| NUS || style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2020/GL1.pdf PDF] || [https://www.comp.nus.edu.sg/~chitrale/ Chitralekha Gupta], [http://ece.nus.edu.sg/drupal/?q=node/159 Haizhou Li]
|-

! ZWZL1
| ZWZL1 || style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2020/ZWZL1.pdf PDF] || [], [], []
|-

! ZWZL2
| ZWZL2 || style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2020/ZWZL1.pdf PDF] || [], [], []
|-

! ZWZL3
| ZWZL3 || style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2020/ZWZL1.pdf PDF] || [], [], []
|-

! DDA1
| Audio2Lyrics_emirdemirel || style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2020/DDA3.pdf PDF] || [http://www.eecs.qmul.ac.uk/profiles/demirelemir.html Emir Demirel]
|-

! CC1
| Mir lab || style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2020/CC1.pdf PDF] || [Chun-Hao]
|-
|}

=Results=
UNDER CONSTRUCTION...

===Hansen's dataset a cappella===
====Summary Results====
<csv>2020/ala/HansensDataset_acappella/summary_HansensDataset_acappella.csv</csv>

====Per-track results====

GGL1
<csv>2020/ala/HansensDataset/GGL1/results.csv</csv>

GGL2
<csv>2020/ala/HansensDataset/GGL2/results.csv</csv>

ZWZL1
<csv>2020/ala/HansensDataset/ZWZL1/results.csv</csv>

ZWZL2
<csv>2020/ala/HansensDataset/ZWZL2/results.csv</csv>

ZWZL3
<csv>2020/ala/HansensDataset/ZWZL3/results.csv</csv>

DDA1
<csv>2020/ala/HansensDataset/DDA1/results.csv</csv>

===Hansen's dataset===
====Summary Results====
<csv>2020/ala/HansensDataset/summary_HansensDataset.csv</csv>

====Per-track results====

GGL1
<csv>2020/ala/HansensDataset/GGL1/results.csv</csv>

GGL2
<csv>2020/ala/HansensDataset/GGL2/results.csv</csv>

ZWZL1
<csv>2020/ala/HansensDataset/ZWZL1/results.csv</csv>

ZWZL2
<csv>2020/ala/HansensDataset/ZWZL2/results.csv</csv>

ZWZL3
<csv>2020/ala/HansensDataset/ZWZL3/results.csv</csv>

DDA1
<csv>2020/ala/HansensDataset/DDA1/results.csv</csv>

===Mauch's dataset===

====Summary Results====
<csv>2020/ala/MauchsDataset/summary_MauchsDataset.csv</csv>

====Per-track results====
GGL1
<csv>2020/ala/MauchsDataset/GGL1/results.csv</csv>

GGL2
<csv>2020/ala/MauchsDataset/GGL2/results.csv</csv>

ZWZL1
<csv>2020/ala/MauchsDataset/ZWZL1/results.csv</csv>

ZWZL2
<csv>2020/ala/MauchsDataset/ZWZL2/results.csv</csv>

ZWZL3
<csv>2020/ala/MauchsDataset/ZWZL3/results.csv</csv>

DDA1
<csv>2020/ala/MauchsDataset/DDA1/results.csv</csv>

===Jamendo dataset===

====Summary Results====
<csv>2020/ala/jamendolyrics/summary_jamendolyrics.csv</csv>

====Per-track results====

GGL1
<csv>2020/ala/jamendolyrics/GGL1/metrics/results.csv</csv>

GGL2
<csv>2020/ala/jamendolyrics/GGL2/metrics/results.csv</csv>

ZWZL1
<csv>2020/ala/jamendolyrics/ZWZL1/metrics/results.csv</csv>

ZWZL2
<csv>2020/ala/jamendolyrics/ZWZL2/metrics/results.csv</csv>

ZWZL3
<csv>2020/ala/jamendolyrics/ZWZL3/metrics/results.csv</csv>

DDA1
<csv>2020/ala/jamendolyrics/DDA1/metrics/results.csv</csv>

2020:Automatic Lyrics-to-Audio Alignment Results

2020-10-17T00:38:39Z

Yun Hao: /* Per-track results */

= General Legend =

{| border="1" cellspacing="0" style="text-align: left; width: 800px;"
|- style="background: yellow"
! width="80" | Sub code
! width="200" | Submission name
! width="80" style="text-align: center;" | Abstract
! width="540" | Contributors
|-

! GGL1
| NUS || style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2020/GL1.pdf PDF] || [https://www.comp.nus.edu.sg/~chitrale/ Chitralekha Gupta], [http://ece.nus.edu.sg/drupal/?q=node/159 Haizhou Li]
|-

! GGL2
| NUS || style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2020/GL1.pdf PDF] || [https://www.comp.nus.edu.sg/~chitrale/ Chitralekha Gupta], [http://ece.nus.edu.sg/drupal/?q=node/159 Haizhou Li]
|-

! ZWZL1
| ZWZL1 || style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2020/ZWZL1.pdf PDF] || [], [], []
|-

! ZWZL2
| ZWZL2 || style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2020/ZWZL1.pdf PDF] || [], [], []
|-

! ZWZL3
| ZWZL3 || style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2020/ZWZL1.pdf PDF] || [], [], []
|-

! DDA1
| Audio2Lyrics_emirdemirel || style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2020/DDA3.pdf PDF] || [http://www.eecs.qmul.ac.uk/profiles/demirelemir.html Emir Demirel]
|-

! CC1
| Mir lab || style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2020/CC1.pdf PDF] || [Chun-Hao]
|-
|}

=Results=
UNDER CONSTRUCTION...

===Hansen's dataset a cappella===
====Summary Results====
<csv>2020/ala/HansensDataset_acappella/summary_HansensDataset_acappella.csv</csv>

====Per-track results====

GGL1
<csv>2020/ala/HansensDataset/GGL1/results.csv</csv>

GGL2
<csv>2020/ala/HansensDataset/GGL2/results.csv</csv>

ZWZL1
<csv>2020/ala/HansensDataset/ZWZL1/results.csv</csv>

ZWZL2
<csv>2020/ala/HansensDataset/ZWZL2/results.csv</csv>

ZWZL3
<csv>2020/ala/HansensDataset/ZWZL3/results.csv</csv>

DDA1
<csv>2020/ala/HansensDataset/DDA1/results.csv</csv>

===Hansen's dataset===
====Summary Results====
<csv>2020/ala/HansensDataset/summary_HansensDataset.csv</csv>

====Per-track results====

GGL1
<csv>2020/ala/HansensDataset/GGL1/results.csv</csv>

GGL2
<csv>2020/ala/HansensDataset/GGL2/results.csv</csv>

ZWZL1
<csv>2020/ala/HansensDataset/ZWZL1/results.csv</csv>

ZWZL2
<csv>2020/ala/HansensDataset/ZWZL2/results.csv</csv>

ZWZL3
<csv>2020/ala/HansensDataset/ZWZL3/results.csv</csv>

DDA1
<csv>2020/ala/HansensDataset/DDA1/results.csv</csv>

===Mauch's dataset===

====Summary Results====
<csv>2020/ala/MauchsDataset/summary_MauchsDataset.csv</csv>

====Per-track results====
GGL1
<csv>2020/ala/MauchsDataset/GGL1/metrics/results.csv</csv>

GGL2
<csv>2020/ala/MauchsDataset/GGL2/metrics/results.csv</csv>

ZWZL1
<csv>2020/ala/MauchsDataset/ZWZL1/metrics/results.csv</csv>

ZWZL2
<csv>2020/ala/MauchsDataset/ZWZL2/metrics/results.csv</csv>

ZWZL3
<csv>2020/ala/MauchsDataset/ZWZL3/metrics/results.csv</csv>

DDA1
<csv>2020/ala/MauchsDataset/DDA1/metrics/results.csv</csv>

===Jamendo dataset===

====Summary Results====
<csv>2020/ala/jamendolyrics/summary_jamendolyrics.csv</csv>

====Per-track results====

GGL1
<csv>2020/ala/jamendolyrics/GGL1/metrics/results.csv</csv>

GGL2
<csv>2020/ala/jamendolyrics/GGL2/metrics/results.csv</csv>

ZWZL1
<csv>2020/ala/jamendolyrics/ZWZL1/metrics/results.csv</csv>

ZWZL2
<csv>2020/ala/jamendolyrics/ZWZL2/metrics/results.csv</csv>

ZWZL3
<csv>2020/ala/jamendolyrics/ZWZL3/metrics/results.csv</csv>

DDA1
<csv>2020/ala/jamendolyrics/DDA1/metrics/results.csv</csv>

2020:Automatic Lyrics-to-Audio Alignment Results

2020-10-17T00:38:20Z

Yun Hao: /* Per-track results */

= General Legend =

{| border="1" cellspacing="0" style="text-align: left; width: 800px;"
|- style="background: yellow"
! width="80" | Sub code
! width="200" | Submission name
! width="80" style="text-align: center;" | Abstract
! width="540" | Contributors
|-

! GGL1
| NUS || style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2020/GL1.pdf PDF] || [https://www.comp.nus.edu.sg/~chitrale/ Chitralekha Gupta], [http://ece.nus.edu.sg/drupal/?q=node/159 Haizhou Li]
|-

! GGL2
| NUS || style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2020/GL1.pdf PDF] || [https://www.comp.nus.edu.sg/~chitrale/ Chitralekha Gupta], [http://ece.nus.edu.sg/drupal/?q=node/159 Haizhou Li]
|-

! ZWZL1
| ZWZL1 || style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2020/ZWZL1.pdf PDF] || [], [], []
|-

! ZWZL2
| ZWZL2 || style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2020/ZWZL1.pdf PDF] || [], [], []
|-

! ZWZL3
| ZWZL3 || style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2020/ZWZL1.pdf PDF] || [], [], []
|-

! DDA1
| Audio2Lyrics_emirdemirel || style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2020/DDA3.pdf PDF] || [http://www.eecs.qmul.ac.uk/profiles/demirelemir.html Emir Demirel]
|-

! CC1
| Mir lab || style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2020/CC1.pdf PDF] || [Chun-Hao]
|-
|}

=Results=
UNDER CONSTRUCTION...

===Hansen's dataset a cappella===
====Summary Results====
<csv>2020/ala/HansensDataset_acappella/summary_HansensDataset_acappella.csv</csv>

====Per-track results====

GGL1
<csv>2020/ala/HansensDataset/GGL1/results.csv</csv>

GGL2
<csv>2020/ala/HansensDataset/GGL2/results.csv</csv>

ZWZL1
<csv>2020/ala/HansensDataset/ZWZL1/results.csv</csv>

ZWZL2
<csv>2020/ala/HansensDataset/ZWZL2/results.csv</csv>

ZWZL3
<csv>2020/ala/HansensDataset/ZWZL3/results.csv</csv>

DDA1
<csv>2020/ala/HansensDataset/DDA1/results.csv</csv>

===Hansen's dataset===
====Summary Results====
<csv>2020/ala/HansensDataset/summary_HansensDataset.csv</csv>

====Per-track results====

GGL1
<csv>2020/ala/HansensDataset/GGL1/metrics/results.csv</csv>

GGL2
<csv>2020/ala/HansensDataset/GGL2/metrics/results.csv</csv>

ZWZL1
<csv>2020/ala/HansensDataset/ZWZL1/metrics/results.csv</csv>

ZWZL2
<csv>2020/ala/HansensDataset/ZWZL2/metrics/results.csv</csv>

ZWZL3
<csv>2020/ala/HansensDataset/ZWZL3/metrics/results.csv</csv>

DDA1
<csv>2020/ala/HansensDataset/DDA1/metrics/results.csv</csv>

===Mauch's dataset===

====Summary Results====
<csv>2020/ala/MauchsDataset/summary_MauchsDataset.csv</csv>

====Per-track results====
GGL1
<csv>2020/ala/MauchsDataset/GGL1/metrics/results.csv</csv>

GGL2
<csv>2020/ala/MauchsDataset/GGL2/metrics/results.csv</csv>

ZWZL1
<csv>2020/ala/MauchsDataset/ZWZL1/metrics/results.csv</csv>

ZWZL2
<csv>2020/ala/MauchsDataset/ZWZL2/metrics/results.csv</csv>

ZWZL3
<csv>2020/ala/MauchsDataset/ZWZL3/metrics/results.csv</csv>

DDA1
<csv>2020/ala/MauchsDataset/DDA1/metrics/results.csv</csv>

===Jamendo dataset===

====Summary Results====
<csv>2020/ala/jamendolyrics/summary_jamendolyrics.csv</csv>

====Per-track results====

GGL1
<csv>2020/ala/jamendolyrics/GGL1/metrics/results.csv</csv>

GGL2
<csv>2020/ala/jamendolyrics/GGL2/metrics/results.csv</csv>

ZWZL1
<csv>2020/ala/jamendolyrics/ZWZL1/metrics/results.csv</csv>

ZWZL2
<csv>2020/ala/jamendolyrics/ZWZL2/metrics/results.csv</csv>

ZWZL3
<csv>2020/ala/jamendolyrics/ZWZL3/metrics/results.csv</csv>

DDA1
<csv>2020/ala/jamendolyrics/DDA1/metrics/results.csv</csv>

2020:MIREX2020 Results

2020-10-15T06:08:31Z

Yun Hao: /* Results by Task (More results are coming) */

==Overall Results Poster==
Coming soon


==Results by Task (More results are coming) ==
* [[2020:Audio Fingerprinting Results|Audio Fingerprinting Results]]

* Audio Melody Extraction Results
** [https://nema.lis.illinois.edu/nema_out/mirex2020/results/ame/adc04/ ADC04 Dataset]  
** [https://nema.lis.illinois.edu/nema_out/mirex2020/results/ame/mrx05/ MIREX05 Dataset]  
** [https://nema.lis.illinois.edu/nema_out/mirex2020/results/ame/ind08/ INDIAN08 Dataset]  
** [https://nema.lis.illinois.edu/nema_out/mirex2020/results/ame/mrx09_0db/ MIREX09 0dB Dataset]  
** [https://nema.lis.illinois.edu/nema_out/mirex2020/results/ame/mrx09_m5db/ MIREX09 -5dB Dataset]  
** [https://nema.lis.illinois.edu/nema_out/mirex2020/results/ame/mrx09_p5db/ MIREX09 +5dB Dataset]  
** [https://nema.lis.illinois.edu/nema_out/mirex2020/results/ame/orchset/ ORCHSET15 Dataset]  

* [https://www.music-ir.org/mirex/wiki/2019:Patterns_for_Prediction_Results Patterns for Prediction Results]  

* [[2020:Audio Cover Song Identification Results|Audio Cover Song Identification Results]]

*Train-Test Task Set
** [https://www.music-ir.org/nema_out/mirex2020/results/act/mood_report/index.html Audio Music Mood Classification Results ]  
** [https://www.music-ir.org/nema_out/mirex2020/results/act/kmoodk_report/ Audio KPOP Mood (Annotated by Korean Annotators) Classification Results ]  
** [https://www.music-ir.org/nema_out/mirex2020/results/act/kmooda_report/ Audio KPOP Mood (Annotated by American Annotators) Classification Results ]  
** [https://www.music-ir.org/nema_out/mirex2020/results/act/mixed_report/ Audio Mixed Popular Genre Classification Results ]  
** [https://www.music-ir.org/nema_out/mirex2020/results/act/kgenrek_report/ Audio KPOP Genre (Annotated by Korean Annotators) Classification Results ]  
** [https://www.music-ir.org/nema_out/mirex2020/results/act/kgenrea_report/ Audio KPOP Genre (Annotated by American Annotators) Classification Results ]  

* [[2020:Automatic Lyrics-to-Audio Alignment Results | Automatic Lyrics-to-Audio Alignment Results]]  
* [[2020:Lyrics Transcription Results | Lyrics Transcription Results]]  

* [[2020:Audio_Key_Detection_Results | Audio Key Detection]]  
* [[2020:Audio_Chord_Estimation_Results | Audio Chord Estimation]]
** [[2020:Audio_Chord_Estimation_Results#Isophonics2009 | Isophonics2009 Dataset]]  
** [[2020:Audio_Chord_Estimation_Results#Billboard2012 | Billboard2012 Dataset]]  
** [[2020:Audio_Chord_Estimation_Results#Billboard_013 | Billboard2013 Dataset]]  
** [[2020:Audio_Chord_Estimation_Results#JayChou29 | JayChou29 Dataset]]  
** [[2020:Audio_Chord_Estimation_Results#RobbieWilliams | RobbieWilliams Dataset]]  
** [[2020:Audio_Chord_Estimation_Results#RWC-Popular | RWC-Popular Dataset]]  
** [[2020:Audio_Chord_Estimation_Results#USPOP2002Chords | USPOP2002Chords Dataset]]  
** [[2020:Audio_Chord_Estimation_Results#CASD-Annotator1 | CASD Dataset]]  

* [[2020:Singing_Transcription_from_Polyphonic_Music_Results | Singing Transcription from Polyphonic Music Results]]

2020:Audio Cover Song Identification Results

2020-10-15T05:51:50Z

Yun Hao:

== Introduction ==

Audio Cover Song (ACS) Identification was evaluated against two datasets: ''Mixed Collection'' and ''Sapp's Mazurka Collection''.

===Mixed Collection Information===
This is the "original" ACS collection. Within the 1000 pieces in the Audio Cover Song database, there are embedded 30 different "cover songs" each represented by 11 different "versions" for a total of 330 audio files (16bit, monophonic, 22.05khz, wav). The "cover songs" represent a variety of genres (e.g., classical, jazz, gospel, rock, folk-rock, etc.) and the variations span a variety of styles and orchestrations.

Using each of these cover song files in turn as the "seed/query" file, we will examine the returned lists of items for the presence of the other 10 versions of the "seed/query" file.

===Sapp's Mazurka Collection Information ===
In addition to our original ACS dataset, we used the [http://www.mazurka.org.uk/ Mazurka.org dataset] put together by Craig Sapp. We randomly chose 11 versions from 49 mazurkas and ran it as a separate ACS subtask. Systems returned a distance matrix of 539x539 from which we located the ranks of each of the associated cover versions.

== General Legend ==
{| border="1" cellspacing="0" style="text-align: left; width: 800px;"
|- style="background: yellow;"
! width="80" | Sub code
! width="200" | Submission name
! width="80" style="text-align: center;" | Abstract
! width="440" | Contributors
|-
! DY1
| SinoNet || style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2020/DY1.pdf PDF] || [http://www.icst.pku.edu.cn Zhesong Yu], Xiaoshuo Xu, [http://www.icst.pku.edu.cn/team/content_266.htm Xiaoou Chen] and Deshun Yang,
|-
! DYZC1
| CasperNet0 || style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2020/DYZC1.pdf PDF] || [https://github.com/diggerdu Xingjian Du], [http://www.icst.pku.edu.cn Zhesong Yu], [http://www.tencent.com/en-us/index.shtml Bilei Zhu], [http://www.icst.pku.edu.cn/team/content_266.htm Xiaoou Chen]
|-
! HCCL1
| CSI task based on Subspace Merging of Enhanced Cross-Similarity Graphs || style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2020/HCCL1.pdf PDF] ||[http://cise.ecust.edu.cn/ Jingyi Hu], [http://cise.ecust.edu.cn/ Ning Chen],[http://www.ecust.edu.cn/ Jialing Cao], [http://www.ecust.edu.cn/ Han Lei]
|-
! ZL1
| ZJ_T1 || style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2020/ZL1.pdf PDF] || [http://ir.netease.com/index.php/ Jian Zhao ], [http://163.com Huaping Liu]
|}

== Results ==

===Mixed Collection===

====Summary Results====
<csv p=2>2020/acs/coversong1000.summary.csv</csv>

====Number of Correct Covers at Rank X Returned in Top Ten====
<csv>2020/acs/coversong1000.toptendist.csv</csv>

====Average Performance per Query Group====
<csv p=2>2020/acs/coversong1000.precision.groups.csv</csv>

===Sapp's Mazuraka Collection===

====Summary results====
<csv p=2>2020/acs/mazurkas.summary.csv</csv>

====Number of Correct Covers at Rank X Returned in Top Ten====
<csv>2020/acs/mazurkas.toptendist.csv</csv>

====Average Performance per Query Group====
<csv p=2>2020/acs/mazurkas.precision.groups.csv</csv>

==Individual Results Files==

===Mixed Collection===
'''Average Precision by Query'''

'''DY1''' : [https://music-ir.org/mirex/results/2020/acs/DY1.coversong1000.avgprec.txt Zhesong Yu, Xiaoshuo Xu, Xiaoou Chen, Deshun Yang] 
'''DYZC1''' : [https://music-ir.org/mirex/results/2020/acs/DYZC1.coversong1000.avgprec.txt Xingjian Du, Zhesong Yu,, Bilei Zhu, Xiaoou Chen] 

'''ZL1''' : [https://music-ir.org/mirex/results/2020/acs/ZL1.coversong1000.avgprec.txt Jian Zhao, Huaping Liu] 

'''Rank Lists'''

'''DY1''' : [https://music-ir.org/mirex/results/2020/acs/DY1.coversong1000.ranklist.txt Zhesong Yu, Xiaoshuo Xu, Xiaoou Chen, Deshun Yang] 
'''DYZC1''' : [https://music-ir.org/mirex/results/2020/acs/DYZC1.coversong1000.ranklist.txt Xingjian Du, Zhesong Yu,, Bilei Zhu, Xiaoou Chen] 

'''ZL1''' : [https://music-ir.org/mirex/results/2020/acs/ZL1.coversong1000.ranklist.txt Jian Zhao, Huaping Liu] 

===Mazurkas===
'''Average Precision by Query'''
'''DY1''' : [https://music-ir.org/mirex/results/2020/acs/DY1.mazurkas.avgprec.txt Zhesong Yu, Xiaoshuo Xu, Xiaoou Chen, Deshun Yang] 
'''DYZC1''' : [https://music-ir.org/mirex/results/2020/acs/DYZC1.mazurkas.avgprec.txt Xingjian Du, Zhesong Yu,, Bilei Zhu, Xiaoou Chen] 
'''HCCL1''' : [https://music-ir.org/mirex/results/2020/acs/HCCL1.mazurkas.avgprec.txt Jingyi Hu, Ning Chen,Jialing Cao, Han Lei] 
'''ZL1''' : [https://music-ir.org/mirex/results/2020/acs/ZL1.mazurkas.avgprec.txt Jian Zhao, Huaping Liu] 

'''Rank Lists'''
'''DY1''' : [https://music-ir.org/mirex/results/2020/acs/DY1.mazurkas.ranklist.txt Zhesong Yu, Xiaoshuo Xu, Xiaoou Chen, Deshun Yang] 
'''DYZC1''' : [https://music-ir.org/mirex/results/2020/acs/DYZC1.mazurkas.ranklist.txt Xingjian Du, Zhesong Yu,, Bilei Zhu, Xiaoou Chen] 
'''HCCL1''' : [https://music-ir.org/mirex/results/2020/acs/HCCL1.mazurkas.ranklist.txt Jingyi Hu, Ning Chen,Jialing Cao, Han Lei] 
'''ZL1''' : [https://music-ir.org/mirex/results/2020/acs/ZL1.mazurkas.ranklist.txt Jian Zhao, Huaping Liu]

2020:Audio Cover Song Identification Results

2020-10-15T05:48:25Z

Yun Hao: Undo revision 13301 by Yun Hao (talk)

== Introduction ==

Audio Cover Song (ACS) Identification was evaluated against two datasets: ''Mixed Collection'' and ''Sapp's Mazurka Collection''.

===Mixed Collection Information===
This is the "original" ACS collection. Within the 1000 pieces in the Audio Cover Song database, there are embedded 30 different "cover songs" each represented by 11 different "versions" for a total of 330 audio files (16bit, monophonic, 22.05khz, wav). The "cover songs" represent a variety of genres (e.g., classical, jazz, gospel, rock, folk-rock, etc.) and the variations span a variety of styles and orchestrations.

Using each of these cover song files in turn as the "seed/query" file, we will examine the returned lists of items for the presence of the other 10 versions of the "seed/query" file.

===Sapp's Mazurka Collection Information ===
In addition to our original ACS dataset, we used the [http://www.mazurka.org.uk/ Mazurka.org dataset] put together by Craig Sapp. We randomly chose 11 versions from 49 mazurkas and ran it as a separate ACS subtask. Systems returned a distance matrix of 539x539 from which we located the ranks of each of the associated cover versions.

== General Legend ==
{| border="1" cellspacing="0" style="text-align: left; width: 800px;"
|- style="background: yellow;"
! width="80" | Sub code
! width="200" | Submission name
! width="80" style="text-align: center;" | Abstract
! width="440" | Contributors
|-
! DY1
| SinoNet || style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2020/DY1.pdf PDF] || [https://github.com/diggerdu Xingjian Du], [http://www.icst.pku.edu.cn Zhesong Yu]
|-
! DYZC1
| CasperNet0 || style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2020/DYZC1.pdf PDF] || [https://github.com/diggerdu Xingjian Du], [http://www.icst.pku.edu.cn Zhesong Yu],, [http://www.tencent.com/en-us/index.shtml Bilei Zhu], [http://www.icst.pku.edu.cn/team/content_266.htm Xiaoou Chen]
|-
! HCCL1
| CSI task based on Subspace Merging of Enhanced Cross-Similarity Graphs || style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2020/HCCL1.pdf PDF] ||[http://cise.ecust.edu.cn/ Jingyi Hu], [http://cise.ecust.edu.cn/ Ning Chen],[http://www.ecust.edu.cn/ Jialing Cao], [http://www.ecust.edu.cn/ Han Lei]
|-
! ZL1
| ZJ_T1 || style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2020/ZL1.pdf PDF] || [http://ir.netease.com/index.php/ Jian Zhao ], [http://163.com Huaping Liu]
|}

== Results ==

===Mixed Collection===

====Summary Results====
<csv p=2>2020/acs/coversong1000.summary.csv</csv>

====Number of Correct Covers at Rank X Returned in Top Ten====
<csv>2020/acs/coversong1000.toptendist.csv</csv>

====Average Performance per Query Group====
<csv p=2>2020/acs/coversong1000.precision.groups.csv</csv>

===Sapp's Mazuraka Collection===

====Summary results====
<csv p=2>2020/acs/mazurkas.summary.csv</csv>

====Number of Correct Covers at Rank X Returned in Top Ten====
<csv>2020/acs/mazurkas.toptendist.csv</csv>

====Average Performance per Query Group====
<csv p=2>2020/acs/mazurkas.precision.groups.csv</csv>

==Individual Results Files==

===Mixed Collection===
'''Average Precision by Query'''

'''DY1''' : [https://music-ir.org/mirex/results/2020/acs/DY1.coversong1000.avgprec.txt Xingjian Du, Zhesong Yu] 
'''DYZC1''' : [https://music-ir.org/mirex/results/2020/acs/DYZC1.coversong1000.avgprec.txt Xingjian Du, Zhesong Yu,, Bilei Zhu, Xiaoou Chen] 

'''ZL1''' : [https://music-ir.org/mirex/results/2020/acs/ZL1.coversong1000.avgprec.txt Jian Zhao, Huaping Liu] 

'''Rank Lists'''

'''DY1''' : [https://music-ir.org/mirex/results/2020/acs/DY1.coversong1000.ranklist.txt Xingjian Du, Zhesong Yu] 
'''DYZC1''' : [https://music-ir.org/mirex/results/2020/acs/DYZC1.coversong1000.ranklist.txt Xingjian Du, Zhesong Yu,, Bilei Zhu, Xiaoou Chen] 

'''ZL1''' : [https://music-ir.org/mirex/results/2020/acs/ZL1.coversong1000.ranklist.txt Jian Zhao, Huaping Liu] 

===Mazurkas===
'''Average Precision by Query'''
'''DY1''' : [https://music-ir.org/mirex/results/2020/acs/DY1.mazurkas.avgprec.txt Xingjian Du, Zhesong Yu] 
'''DYZC1''' : [https://music-ir.org/mirex/results/2020/acs/DYZC1.mazurkas.avgprec.txt Xingjian Du, Zhesong Yu,, Bilei Zhu, Xiaoou Chen] 
'''HCCL1''' : [https://music-ir.org/mirex/results/2020/acs/HCCL1.mazurkas.avgprec.txt Jingyi Hu, Ning Chen,Jialing Cao, Han Lei] 
'''ZL1''' : [https://music-ir.org/mirex/results/2020/acs/ZL1.mazurkas.avgprec.txt Jian Zhao, Huaping Liu] 

'''Rank Lists'''
'''DY1''' : [https://music-ir.org/mirex/results/2020/acs/DY1.mazurkas.ranklist.txt Xingjian Du, Zhesong Yu] 
'''DYZC1''' : [https://music-ir.org/mirex/results/2020/acs/DYZC1.mazurkas.ranklist.txt Xingjian Du, Zhesong Yu,, Bilei Zhu, Xiaoou Chen] 
'''HCCL1''' : [https://music-ir.org/mirex/results/2020/acs/HCCL1.mazurkas.ranklist.txt Jingyi Hu, Ning Chen,Jialing Cao, Han Lei] 
'''ZL1''' : [https://music-ir.org/mirex/results/2020/acs/ZL1.mazurkas.ranklist.txt Jian Zhao, Huaping Liu]

2020:Audio Cover Song Identification Results

2020-10-15T05:33:54Z

Yun Hao: /* General Legend */

== Introduction ==

Audio Cover Song (ACS) Identification was evaluated against two datasets: ''Mixed Collection'' and ''Sapp's Mazurka Collection''.

===Mixed Collection Information===
This is the "original" ACS collection. Within the 1000 pieces in the Audio Cover Song database, there are embedded 30 different "cover songs" each represented by 11 different "versions" for a total of 330 audio files (16bit, monophonic, 22.05khz, wav). The "cover songs" represent a variety of genres (e.g., classical, jazz, gospel, rock, folk-rock, etc.) and the variations span a variety of styles and orchestrations.

Using each of these cover song files in turn as the "seed/query" file, we will examine the returned lists of items for the presence of the other 10 versions of the "seed/query" file.

===Sapp's Mazurka Collection Information ===
In addition to our original ACS dataset, we used the [http://www.mazurka.org.uk/ Mazurka.org dataset] put together by Craig Sapp. We randomly chose 11 versions from 49 mazurkas and ran it as a separate ACS subtask. Systems returned a distance matrix of 539x539 from which we located the ranks of each of the associated cover versions.

== General Legend ==
{| border="1" cellspacing="0" style="text-align: left; width: 800px;"
|- style="background: yellow;"
! width="80" | Sub code
! width="200" | Submission name
! width="80" style="text-align: center;" | Abstract
! width="440" | Contributors
|-
! DY1
| SinoNet || style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2020/DY1.pdf PDF] || [https://github.com/diggerdu Xingjian Du], [http://www.icst.pku.edu.cn Zhesong Yu]
|-
! DYZC1
| CasperNet0 || style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2020/DYZC1.pdf PDF] || [http://www.icst.pku.edu.cn Zhesong Yu], Xiaoshuo Xu, [http://www.icst.pku.edu.cn/team/content_266.htm Xiaoou Chen] and Deshun Yang,
|-
! HCCL1
| CSI task based on Subspace Merging of Enhanced Cross-Similarity Graphs || style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2020/HCCL1.pdf PDF] ||[http://cise.ecust.edu.cn/ Jingyi Hu], [http://cise.ecust.edu.cn/ Ning Chen],[http://www.ecust.edu.cn/ Jialing Cao], [http://www.ecust.edu.cn/ Han Lei]
|-
! ZL1
| ZJ_T1 || style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2020/ZL1.pdf PDF] || [http://ir.netease.com/index.php/ Jian Zhao ], [http://163.com Huaping Liu]
|}

== Results ==

===Mixed Collection===

====Summary Results====
<csv p=2>2020/acs/coversong1000.summary.csv</csv>

====Number of Correct Covers at Rank X Returned in Top Ten====
<csv>2020/acs/coversong1000.toptendist.csv</csv>

====Average Performance per Query Group====
<csv p=2>2020/acs/coversong1000.precision.groups.csv</csv>

===Sapp's Mazuraka Collection===

====Summary results====
<csv p=2>2020/acs/mazurkas.summary.csv</csv>

====Number of Correct Covers at Rank X Returned in Top Ten====
<csv>2020/acs/mazurkas.toptendist.csv</csv>

====Average Performance per Query Group====
<csv p=2>2020/acs/mazurkas.precision.groups.csv</csv>

==Individual Results Files==

===Mixed Collection===
'''Average Precision by Query'''

'''DY1''' : [https://music-ir.org/mirex/results/2020/acs/DY1.coversong1000.avgprec.txt Xingjian Du, Zhesong Yu] 
'''DYZC1''' : [https://music-ir.org/mirex/results/2020/acs/DYZC1.coversong1000.avgprec.txt Xingjian Du, Zhesong Yu,, Bilei Zhu, Xiaoou Chen] 

'''ZL1''' : [https://music-ir.org/mirex/results/2020/acs/ZL1.coversong1000.avgprec.txt Jian Zhao, Huaping Liu] 

'''Rank Lists'''

'''DY1''' : [https://music-ir.org/mirex/results/2020/acs/DY1.coversong1000.ranklist.txt Xingjian Du, Zhesong Yu] 
'''DYZC1''' : [https://music-ir.org/mirex/results/2020/acs/DYZC1.coversong1000.ranklist.txt Xingjian Du, Zhesong Yu,, Bilei Zhu, Xiaoou Chen] 

'''ZL1''' : [https://music-ir.org/mirex/results/2020/acs/ZL1.coversong1000.ranklist.txt Jian Zhao, Huaping Liu] 

===Mazurkas===
'''Average Precision by Query'''
'''DY1''' : [https://music-ir.org/mirex/results/2020/acs/DY1.mazurkas.avgprec.txt Xingjian Du, Zhesong Yu] 
'''DYZC1''' : [https://music-ir.org/mirex/results/2020/acs/DYZC1.mazurkas.avgprec.txt Xingjian Du, Zhesong Yu,, Bilei Zhu, Xiaoou Chen] 
'''HCCL1''' : [https://music-ir.org/mirex/results/2020/acs/HCCL1.mazurkas.avgprec.txt Jingyi Hu, Ning Chen,Jialing Cao, Han Lei] 
'''ZL1''' : [https://music-ir.org/mirex/results/2020/acs/ZL1.mazurkas.avgprec.txt Jian Zhao, Huaping Liu] 

'''Rank Lists'''
'''DY1''' : [https://music-ir.org/mirex/results/2020/acs/DY1.mazurkas.ranklist.txt Xingjian Du, Zhesong Yu] 
'''DYZC1''' : [https://music-ir.org/mirex/results/2020/acs/DYZC1.mazurkas.ranklist.txt Xingjian Du, Zhesong Yu,, Bilei Zhu, Xiaoou Chen] 
'''HCCL1''' : [https://music-ir.org/mirex/results/2020/acs/HCCL1.mazurkas.ranklist.txt Jingyi Hu, Ning Chen,Jialing Cao, Han Lei] 
'''ZL1''' : [https://music-ir.org/mirex/results/2020/acs/ZL1.mazurkas.ranklist.txt Jian Zhao, Huaping Liu]

2020:MIREX2020 Results

2020-10-14T21:47:22Z

Yun Hao: /* Results by Task (More results are coming) */

==Overall Results Poster==
Coming soon


==Results by Task (More results are coming) ==
* [[2020:Audio Fingerprinting Results|Audio Fingerprinting Results]]

* Audio Melody Extraction Results
** [https://nema.lis.illinois.edu/nema_out/mirex2020/results/ame/adc04/ ADC04 Dataset]  
** [https://nema.lis.illinois.edu/nema_out/mirex2020/results/ame/mrx05/ MIREX05 Dataset]  
** [https://nema.lis.illinois.edu/nema_out/mirex2020/results/ame/ind08/ INDIAN08 Dataset]  
** [https://nema.lis.illinois.edu/nema_out/mirex2020/results/ame/mrx09_0db/ MIREX09 0dB Dataset]  
** [https://nema.lis.illinois.edu/nema_out/mirex2020/results/ame/mrx09_m5db/ MIREX09 -5dB Dataset]  
** [https://nema.lis.illinois.edu/nema_out/mirex2020/results/ame/mrx09_p5db/ MIREX09 +5dB Dataset]  
** [https://nema.lis.illinois.edu/nema_out/mirex2020/results/ame/orchset/ ORCHSET15 Dataset]  

* [https://www.music-ir.org/mirex/wiki/2019:Patterns_for_Prediction_Results Patterns for Prediction Results]  

* [[2020:Audio Cover Song Identification Results|Audio Cover Song Identification Results]]

*Train-Test Task Set
** [https://www.music-ir.org/nema_out/mirex2020/results/act/mood_report/index.html Audio Music Mood Classification Results ]  


** [https://www.music-ir.org/nema_out/mirex2020/results/act/mixed_report/ Audio Mixed Popular Genre Classification Results ]  
** [https://www.music-ir.org/nema_out/mirex2020/results/act/kgenrek_report/ Audio KPOP Genre (Annotated by Korean Annotators) Classification Results ]  
** [https://www.music-ir.org/nema_out/mirex2020/results/act/kgenrea_report/ Audio KPOP Genre (Annotated by American Annotators) Classification Results ]  

* [[2020:Automatic Lyrics-to-Audio Alignment Results | Automatic Lyrics-to-Audio Alignment Results]]  
* [[2020:Lyrics Transcription Results | Lyrics Transcription Results]]  

* [[2020:Audio_Key_Detection_Results | Audio Key Detection]]  
* [[2020:Audio_Chord_Estimation_Results | Audio Chord Estimation]]
** [[2020:Audio_Chord_Estimation_Results#Isophonics2009 | Isophonics2009 Dataset]]  
** [[2020:Audio_Chord_Estimation_Results#Billboard2012 | Billboard2012 Dataset]]  
** [[2020:Audio_Chord_Estimation_Results#Billboard_013 | Billboard2013 Dataset]]  
** [[2020:Audio_Chord_Estimation_Results#JayChou29 | JayChou29 Dataset]]  
** [[2020:Audio_Chord_Estimation_Results#RobbieWilliams | RobbieWilliams Dataset]]  
** [[2020:Audio_Chord_Estimation_Results#RWC-Popular | RWC-Popular Dataset]]  
** [[2020:Audio_Chord_Estimation_Results#USPOP2002Chords | USPOP2002Chords Dataset]]  
** [[2020:Audio_Chord_Estimation_Results#CASD-Annotator1 | CASD Dataset]]  

* [[2020:Singing_Transcription_from_Polyphonic_Music_Results | Singing Transcription from Polyphonic Music Results]]

2020:MIREX2020 Results

2020-10-14T21:36:11Z

Yun Hao: /* Results by Task (More results are coming) */

==Overall Results Poster==
Coming soon


==Results by Task (More results are coming) ==
* [[2020:Audio Fingerprinting Results|Audio Fingerprinting Results]]

* Audio Melody Extraction Results
** [https://nema.lis.illinois.edu/nema_out/mirex2020/results/ame/adc04/ ADC04 Dataset]  
** [https://nema.lis.illinois.edu/nema_out/mirex2020/results/ame/mrx05/ MIREX05 Dataset]  
** [https://nema.lis.illinois.edu/nema_out/mirex2020/results/ame/ind08/ INDIAN08 Dataset]  
** [https://nema.lis.illinois.edu/nema_out/mirex2020/results/ame/mrx09_0db/ MIREX09 0dB Dataset]  
** [https://nema.lis.illinois.edu/nema_out/mirex2020/results/ame/mrx09_m5db/ MIREX09 -5dB Dataset]  
** [https://nema.lis.illinois.edu/nema_out/mirex2020/results/ame/mrx09_p5db/ MIREX09 +5dB Dataset]  
** [https://nema.lis.illinois.edu/nema_out/mirex2020/results/ame/orchset/ ORCHSET15 Dataset]  

* [https://www.music-ir.org/mirex/wiki/2019:Patterns_for_Prediction_Results Patterns for Prediction Results]  

* [[2020:Audio Cover Song Identification Results|Audio Cover Song Identification Results]]

*Train-Test Task Set
** [https://www.music-ir.org/nema_out/mirex2020/results/act/mood_report/index.html Audio Music Mood Classification Results ]  


** [https://www.music-ir.org/nema_out/mirex2020/results/act/mixed_report/ Audio Mixed Popular Genre Classification Results ]  



* [[2020:Automatic Lyrics-to-Audio Alignment Results | Automatic Lyrics-to-Audio Alignment Results]]  
* [[2020:Lyrics Transcription Results | Lyrics Transcription Results]]  

* [[2020:Audio_Key_Detection_Results | Audio Key Detection]]  
* [[2020:Audio_Chord_Estimation_Results | Audio Chord Estimation]]
** [[2020:Audio_Chord_Estimation_Results#Isophonics2009 | Isophonics2009 Dataset]]  
** [[2020:Audio_Chord_Estimation_Results#Billboard2012 | Billboard2012 Dataset]]  
** [[2020:Audio_Chord_Estimation_Results#Billboard_013 | Billboard2013 Dataset]]  
** [[2020:Audio_Chord_Estimation_Results#JayChou29 | JayChou29 Dataset]]  
** [[2020:Audio_Chord_Estimation_Results#RobbieWilliams | RobbieWilliams Dataset]]  
** [[2020:Audio_Chord_Estimation_Results#RWC-Popular | RWC-Popular Dataset]]  
** [[2020:Audio_Chord_Estimation_Results#USPOP2002Chords | USPOP2002Chords Dataset]]  
** [[2020:Audio_Chord_Estimation_Results#CASD-Annotator1 | CASD Dataset]]  

* [[2020:Singing_Transcription_from_Polyphonic_Music_Results | Singing Transcription from Polyphonic Music Results]]

2020:MIREX2020 Results

2020-10-14T21:32:00Z

Yun Hao:

==Overall Results Poster==
Coming soon


==Results by Task (More results are coming) ==
* [[2020:Audio Fingerprinting Results|Audio Fingerprinting Results]]

* Audio Melody Extraction Results
** [https://nema.lis.illinois.edu/nema_out/mirex2020/results/ame/adc04/ ADC04 Dataset]  
** [https://nema.lis.illinois.edu/nema_out/mirex2020/results/ame/mrx05/ MIREX05 Dataset]  
** [https://nema.lis.illinois.edu/nema_out/mirex2020/results/ame/ind08/ INDIAN08 Dataset]  
** [https://nema.lis.illinois.edu/nema_out/mirex2020/results/ame/mrx09_0db/ MIREX09 0dB Dataset]  
** [https://nema.lis.illinois.edu/nema_out/mirex2020/results/ame/mrx09_m5db/ MIREX09 -5dB Dataset]  
** [https://nema.lis.illinois.edu/nema_out/mirex2020/results/ame/mrx09_p5db/ MIREX09 +5dB Dataset]  
** [https://nema.lis.illinois.edu/nema_out/mirex2020/results/ame/orchset/ ORCHSET15 Dataset]  

* [https://www.music-ir.org/mirex/wiki/2019:Patterns_for_Prediction_Results Patterns for Prediction Results]  

* [[2020:Audio Cover Song Identification Results|Audio Cover Song Identification Results]]

*Train-Test Task Set
** [https://www.music-ir.org/nema_out/mirex2020/results/act/mood_report/index.html Audio Music Mood Classification Results ]  






* [[2020:Automatic Lyrics-to-Audio Alignment Results | Automatic Lyrics-to-Audio Alignment Results]]  
* [[2020:Lyrics Transcription Results | Lyrics Transcription Results]]  

* [[2020:Audio_Key_Detection_Results | Audio Key Detection]]  
* [[2020:Audio_Chord_Estimation_Results | Audio Chord Estimation]]
** [[2020:Audio_Chord_Estimation_Results#Isophonics2009 | Isophonics2009 Dataset]]  
** [[2020:Audio_Chord_Estimation_Results#Billboard2012 | Billboard2012 Dataset]]  
** [[2020:Audio_Chord_Estimation_Results#Billboard_013 | Billboard2013 Dataset]]  
** [[2020:Audio_Chord_Estimation_Results#JayChou29 | JayChou29 Dataset]]  
** [[2020:Audio_Chord_Estimation_Results#RobbieWilliams | RobbieWilliams Dataset]]  
** [[2020:Audio_Chord_Estimation_Results#RWC-Popular | RWC-Popular Dataset]]  
** [[2020:Audio_Chord_Estimation_Results#USPOP2002Chords | USPOP2002Chords Dataset]]  
** [[2020:Audio_Chord_Estimation_Results#CASD-Annotator1 | CASD Dataset]]  

* [[2020:Singing_Transcription_from_Polyphonic_Music_Results | Singing Transcription from Polyphonic Music Results]]

2019:MIREX2019 Results

2020-10-14T21:30:59Z

Yun Hao: /* Overall Results Poster */

==Overall Results Poster==
[https://www.music-ir.org/mirex/results/2019/MIREX2019Poster.pdf MIREX 2019 Results Poster (PDF)]

==Results by Task (More results are coming) ==
* Multiple Fundamental Frequency Estimation & Tracking Results
** [[2019:Multiple_Fundamental_Frequency_Estimation_%26_Tracking_Results_%2D_MIREX_Dataset | MIREX Dataset]]  
** [[2019:Multiple_Fundamental_Frequency_Estimation_%26_Tracking_Results_%2D_Su_Dataset | Su Dataset]]  
* [https://www.music-ir.org/mirex/wiki/2019:Music_Detection_Results Music Detection Results]  
* [https://www.music-ir.org/mirex/wiki/2019:Patterns_for_Prediction_Results Patterns for Prediction Results]  
* Audio Melody Extraction Results
** [https://nema.lis.illinois.edu/nema_out/mirex2019/results/ame/adc04/ ADC04 Dataset]  
** [https://nema.lis.illinois.edu/nema_out/mirex2019/results/ame/mrx05/ MIREX05 Dataset]  
** [https://nema.lis.illinois.edu/nema_out/mirex2019/results/ame/ind08/ INDIAN08 Dataset]  
** [https://nema.lis.illinois.edu/nema_out/mirex2019/results/ame/mrx09_0db/ MIREX09 0dB Dataset]  
** [https://nema.lis.illinois.edu/nema_out/mirex2019/results/ame/mrx09_m5db/ MIREX09 -5dB Dataset]  
** [https://nema.lis.illinois.edu/nema_out/mirex2019/results/ame/mrx09_p5db/ MIREX09 +5dB Dataset]  
** [https://nema.lis.illinois.edu/nema_out/mirex2019/results/ame/orchset/ ORCHSET15 Dataset]  
* [[2019:Automatic Lyrics-to-Audio Alignment Results | Automatic Lyrics-to-Audio Alignment Results]]  
* [[2019:Drum_Transcription_Results | Drum Transcription]]  
* [[2019:Audio Fingerprinting Results|Audio Fingerprinting Results]]
* [[2019:Audio_Key_Detection_Results | Audio Key Detection]]  
* [[2019:Audio_Chord_Estimation_Results | Audio Chord Estimation]]
** [[2019:Audio_Chord_Estimation_Results#Isophonics2009 | Isophonics2009 Dataset]]  
** [[2019:Audio_Chord_Estimation_Results#Billboard2012 | Billboard2012 Dataset]]  
** [[2019:Audio_Chord_Estimation_Results#Billboard_013 | Billboard2013 Dataset]]  
** [[2019:Audio_Chord_Estimation_Results#JayChou29 | JayChou29 Dataset]]  
** [[2019:Audio_Chord_Estimation_Results#RobbieWilliams | RobbieWilliams Dataset]]  
** [[2019:Audio_Chord_Estimation_Results#RWC-Popular | RWC-Popular Dataset]]  
** [[2019:Audio_Chord_Estimation_Results#USPOP2002Chords | USPOP2002Chords Dataset]]  
** [[2019:Audio_Chord_Estimation_Results#CASD-Annotator1 | CASD Dataset]]  
*Train-Test Task Set
** [https://www.music-ir.org/nema_out/mirex2019/results/act/composer_report/ Audio Classical Composer Identification Results ]  
** [https://www.music-ir.org/nema_out/mirex2019/results/act/latin_report/ Audio Latin Genre Classification Results ]  
** [https://www.music-ir.org/nema_out/mirex2019/results/act/mood_report/index.html Audio Music Mood Classification Results ]  
** [https://www.music-ir.org/nema_out/mirex2019/results/act/mixed_report/ Audio Mixed Popular Genre Classification Results ]  
** [https://www.music-ir.org/nema_out/mirex2019/results/act/kgenrek_report/ Audio KPOP Genre (Annotated by Korean Annotators) Classification Results ]  
** [https://www.music-ir.org/nema_out/mirex2019/results/act/kgenrea_report/ Audio KPOP Genre (Annotated by American Annotators) Classification Results ]  
** [https://www.music-ir.org/nema_out/mirex2019/results/act/kmoodk_report/ Audio KPOP Mood (Annotated by Korean Annotators) Classification Results ]  
** [https://www.music-ir.org/nema_out/mirex2019/results/act/kmooda_report/ Audio KPOP Mood (Annotated by American Annotators) Classification Results ]  

* Audio Beat Tracking Results
** [https://nema.lis.illinois.edu/nema_out/mirex2019/results/abt/smc/ SMC Dataset]  
** [https://nema.lis.illinois.edu/nema_out/mirex2019/results/abt/maz/ MAZ Dataset]  

* [[2019:Audio Cover Song Identification Results|Audio Cover Song Identification Results]]

2018:MIREX2018 Results

2020-10-14T21:18:43Z

Yun Hao: /* Overall Results Poster */

==Overall Results Poster==
[https://www.music-ir.org/mirex/results/2018/MIREX2018Poster.pdf MIREX 2018 Results Poster (PDF)]

==Results by Task (More results are coming) ==
* Audio Melody Extraction Results
** [https://nema.lis.illinois.edu/nema_out/mirex2018/results/ame/adc04/ ADC04 Dataset]  
** [https://nema.lis.illinois.edu/nema_out/mirex2018/results/ame/mrx05/ MIREX05 Dataset]  
** [https://nema.lis.illinois.edu/nema_out/mirex2018/results/ame/ind08/ INDIAN08 Dataset]  
** [https://nema.lis.illinois.edu/nema_out/mirex2018/results/ame/mrx09_0db/ MIREX09 0dB Dataset]  
** [https://nema.lis.illinois.edu/nema_out/mirex2018/results/ame/mrx09_m5db/ MIREX09 -5dB Dataset]  
** [https://nema.lis.illinois.edu/nema_out/mirex2018/results/ame/mrx09_p5db/ MIREX09 +5dB Dataset]  
** [https://nema.lis.illinois.edu/nema_out/mirex2018/results/ame/orchset/ ORCHSET15 Dataset]  

* [[2018:Audio Fingerprinting Results|Audio Fingerprinting Results]]
*Train-Test Task Set
** [https://www.music-ir.org/nema_out/mirex2018/results/act/mood_report/index.html Audio Music Mood Classification Results ]  
** [https://www.music-ir.org/nema_out/mirex2018/results/act/kmooda_report/ Audio KPOP Mood (Annotated by American Annotators) Classification Results ]  
** [https://www.music-ir.org/nema_out/mirex2018/results/act/kmoodk_report/ Audio KPOP Mood (Annotated by Korean Annotators) Classification Results ]  
** [https://www.music-ir.org/nema_out/mirex2018/results/act/kgenrek_report/ Audio KPOP Genre (Annotated by Korean Annotators) Classification Results ]  

* [[2018:Automatic Lyrics-to-Audio Alignment Results | Automatic Lyrics-to-Audio Alignment Results]]

* Multiple Fundamental Frequency Estimation & Tracking Results
** [[2018:Multiple_Fundamental_Frequency_Estimation_%26_Tracking_Results_%2D_MIREX_Dataset | MIREX Dataset]]  
** [[2018:Multiple_Fundamental_Frequency_Estimation_%26_Tracking_Results_%2D_Su_Dataset | Su Dataset]]  

* [https://nema.lis.illinois.edu/nema_out/mirex2018/results/aod/ Audio Onset Detection Results]  
* [[2018:Audio Cover Song Identification Results|Audio Cover Song Identification Results]]

* [[2018:Drum_Transcription_Results | Drum Transcription]]  
* [[2018:Patterns for Prediction Results|Patterns for Prediction Results]]

* [https://www.music-ir.org/mirex/wiki/2018:Music_and_or_Speech_Detection_Results Music and/or Speech Detection]

* Audio Beat Tracking Results
** [https://nema.lis.illinois.edu/nema_out/mirex2018/results/abt/smc/ SMC Dataset]  
** [https://nema.lis.illinois.edu/nema_out/mirex2018/results/abt/maz/ MAZ Dataset]  
** [https://nema.lis.illinois.edu/nema_out/mirex2018/results/abt/mck/ MCK Dataset]  

* [[2018:Audio_Key_Detection_Results | Audio Key Detection]]  
* [[2018:Audio_Chord_Estimation_Results | Audio Chord Estimation]]
** [[2018:Audio_Chord_Estimation_Results#Isophonics2009 | Isophonics2009 Dataset]]  
** [[2018:Audio_Chord_Estimation_Results#Billboard2012 | Billboard2012 Dataset]]  
** [[2018:Audio_Chord_Estimation_Results#Billboard_013 | Billboard2013 Dataset]]  
** [[2018:Audio_Chord_Estimation_Results#JayChou29 | JayChou29 Dataset]]  
** [[2018:Audio_Chord_Estimation_Results#RobbieWilliams | RobbieWilliams Dataset]]  
** [[2018:Audio_Chord_Estimation_Results#RWC-Popular | RWC-Popular Dataset]]  
** [[2018:Audio_Chord_Estimation_Results#USPOP2002Chords | USPOP2002Chords Dataset]]  

* Audio Tempo Estimation Results
** [https://nema.lis.illinois.edu/nema_out/mirex2018/results/ate/mck/ MIREX 06 Dataset Results]  
** [https://nema.lis.illinois.edu/nema_out/mirex2018/results/ate/giants/ Giants Dataset Results]  

2020:MIREX2020 Results

2020-10-14T21:08:08Z

Yun Hao: /* Results by Task (More results are coming) */

==Results by Task (More results are coming) ==
* [[2020:Audio Fingerprinting Results|Audio Fingerprinting Results]]

* Audio Melody Extraction Results
** [https://nema.lis.illinois.edu/nema_out/mirex2020/results/ame/adc04/ ADC04 Dataset]  
** [https://nema.lis.illinois.edu/nema_out/mirex2020/results/ame/mrx05/ MIREX05 Dataset]  
** [https://nema.lis.illinois.edu/nema_out/mirex2020/results/ame/ind08/ INDIAN08 Dataset]  
** [https://nema.lis.illinois.edu/nema_out/mirex2020/results/ame/mrx09_0db/ MIREX09 0dB Dataset]  
** [https://nema.lis.illinois.edu/nema_out/mirex2020/results/ame/mrx09_m5db/ MIREX09 -5dB Dataset]  
** [https://nema.lis.illinois.edu/nema_out/mirex2020/results/ame/mrx09_p5db/ MIREX09 +5dB Dataset]  
** [https://nema.lis.illinois.edu/nema_out/mirex2020/results/ame/orchset/ ORCHSET15 Dataset]  

* [https://www.music-ir.org/mirex/wiki/2019:Patterns_for_Prediction_Results Patterns for Prediction Results]  

* [[2020:Audio Cover Song Identification Results|Audio Cover Song Identification Results]]

*Train-Test Task Set
** [https://www.music-ir.org/nema_out/mirex2020/results/act/mood_report/index.html Audio Music Mood Classification Results ]  






* [[2020:Automatic Lyrics-to-Audio Alignment Results | Automatic Lyrics-to-Audio Alignment Results]]  
* [[2020:Lyrics Transcription Results | Lyrics Transcription Results]]  

* [[2020:Audio_Key_Detection_Results | Audio Key Detection]]  
* [[2020:Audio_Chord_Estimation_Results | Audio Chord Estimation]]
** [[2020:Audio_Chord_Estimation_Results#Isophonics2009 | Isophonics2009 Dataset]]  
** [[2020:Audio_Chord_Estimation_Results#Billboard2012 | Billboard2012 Dataset]]  
** [[2020:Audio_Chord_Estimation_Results#Billboard_013 | Billboard2013 Dataset]]  
** [[2020:Audio_Chord_Estimation_Results#JayChou29 | JayChou29 Dataset]]  
** [[2020:Audio_Chord_Estimation_Results#RobbieWilliams | RobbieWilliams Dataset]]  
** [[2020:Audio_Chord_Estimation_Results#RWC-Popular | RWC-Popular Dataset]]  
** [[2020:Audio_Chord_Estimation_Results#USPOP2002Chords | USPOP2002Chords Dataset]]  
** [[2020:Audio_Chord_Estimation_Results#CASD-Annotator1 | CASD Dataset]]  

* [[2020:Singing_Transcription_from_Polyphonic_Music_Results | Singing Transcription from Polyphonic Music Results]]

2020:MIREX2020 Results

2020-10-14T21:07:49Z

Yun Hao: /* Results by Task (More results are coming) */

2020:MIREX2020 Results

2020-10-14T19:42:08Z

Yun Hao: /* Results by Task (More results are coming) */

2020:Singing Transcription from Polyphonic Music Results

2020-10-14T19:41:12Z

Yun Hao: Created page with "== Introduction == These are the results for the 2020 running of the Singing Transcription from Polyphonic Music task. For background information about this task set please re..."

== Introduction ==
These are the results for the 2020 running of the Singing Transcription from Polyphonic Music task. For background information about this task set please refer to the [[2020:Singing Transcription from Polyphonic Music]] page.

== General Legend ==
{| border="1" cellspacing="0" style="text-align: left; width: 800px;"
|- style="background: yellow"
! width="80" | Sub code
! width="200" | Submission name
! width="80" style="text-align: center;" | Abstract
! width="540" | Contributors
|-
! HZ3
| HZ_SingTranscription || style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2020/HZ3.pdf PDF] || He Zhuang
|}

==Summary Results==

Please refer to [[2020:Singing Transcription from Polyphonic Music#Evaluation]] section for a detailed explanation for the evaluation metrics.

Cmedia Training Set:
<csv>2020/stpm/stpm_train_result.csv</csv>

Cmedia Test Set:
<csv>2020/stpm/stpm_test_result.csv</csv>

2020:Audio Chord Estimation Results

2020-10-14T19:26:11Z

Yun Hao: /* Algorithmic Output */

==Introduction==

This page contains the results of the 2020 edition of the MIREX automatic chord estimation tasks. This edition was the eighth one since the reorganization of the evaluation procedure in 2013. The results can therefore be directly compared to those of the last six years. Chord labels are evaluated according to five different chord vocabularies and the segmentation is also assessed. Additional information about the used measures can be found on the page of the [[2013:Audio_Chord_Estimation_Results_MIREX_2009 | 2013 edition]].

==What’s new?==
* All datasets and evaluation procedures are the same as last year's MIREX.

==Software==
All software used for the evaluation has been made open-source. The evaluation framework is described by [http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6637748 Pauwels and Peeters (2013)]. The corresponding binaries and code repository can be found on [https://github.com/jpauwels/MusOOEvaluator GitHub] and the used measures are available as presets. The raw algorithmic output provided below makes it possible to calculate the additional measures from the paper (separate results for tetrads, etc.), in addition to those presented below. More help can be found in the [https://github.com/jpauwels/MusOOEvaluator/blob/master/README.md readme].

The statistical comparison between the different submissions is explained in [http://www.terasoft.com.tw/conf/ismir2014/proceedings/T095_250_Paper.pdf Burgoyne et al. (2014)]. The software is available at [https://bitbucket.org/jaburgoyne/mirexace BitBucket]. It uses the detailed results provided below as input.

==Submissions==

{| class="wikitable"
!
! Abstract
! Contributors
|-
| HL2
| style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2020/HL2.pdf PDF]
| [http://mirlag.org Yuan-Hao Ku], [http://mirlag.org Hsueh-Han Lee]
|}

==Results==

===Summary===

All figures can be interpreted as percentages and range from 0 (worst) to 100 (best).

=====Isophonics2009=====
<csv>2020/ace/2020-Isophonics2009.csv</csv>
=====Billboard2012=====
<csv>2020/ace/2020-Billboard2012.csv</csv>
=====Billboard2013=====
<csv>2020/ace/2020-Billboard2013.csv</csv>
=====JayChou29=====
<csv>2020/ace/2020-JayChou29.csv</csv>
=====RobbieWilliams=====
<csv>2020/ace/2020-RobbieWilliams.csv</csv>
=====RWC-Popular=====
<csv>2020/ace/2020-RWC-Popular.csv</csv>
=====USPOP2002Chords=====
<csv>2020/ace/2020-USPOP2002Chords.csv</csv>
=====CASD-Annotator1=====
<csv>2020/ace/2020-CASD-Annotator1.csv</csv>
=====CASD-Annotator2=====
<csv>2020/ace/2020-CASD-Annotator2.csv</csv>
=====CASD-Annotator3=====
<csv>2020/ace/2020-CASD-Annotator3.csv</csv>
=====CASD-Annotator4=====
<csv>2020/ace/2020-CASD-Annotator4.csv</csv>



===Detailed Results===

More details about the performance of the algorithms, including per-song performance and supplementary statistics, are available from [https://github.com/ismir-mirex/ace-results/tree/master/2020 this repository].
.

===Algorithmic Output===

The raw output of the algorithms are available in [https://github.com/ismir-mirex/ace-output/tree/master/2020 this repository]. They can be used to experiment with alternative evaluation measures and statistics.

2020:Audio Chord Estimation Results

2020-10-14T19:26:03Z

Yun Hao: /* Detailed Results */

==Introduction==

This page contains the results of the 2020 edition of the MIREX automatic chord estimation tasks. This edition was the eighth one since the reorganization of the evaluation procedure in 2013. The results can therefore be directly compared to those of the last six years. Chord labels are evaluated according to five different chord vocabularies and the segmentation is also assessed. Additional information about the used measures can be found on the page of the [[2013:Audio_Chord_Estimation_Results_MIREX_2009 | 2013 edition]].

==What’s new?==
* All datasets and evaluation procedures are the same as last year's MIREX.

==Software==
All software used for the evaluation has been made open-source. The evaluation framework is described by [http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6637748 Pauwels and Peeters (2013)]. The corresponding binaries and code repository can be found on [https://github.com/jpauwels/MusOOEvaluator GitHub] and the used measures are available as presets. The raw algorithmic output provided below makes it possible to calculate the additional measures from the paper (separate results for tetrads, etc.), in addition to those presented below. More help can be found in the [https://github.com/jpauwels/MusOOEvaluator/blob/master/README.md readme].

The statistical comparison between the different submissions is explained in [http://www.terasoft.com.tw/conf/ismir2014/proceedings/T095_250_Paper.pdf Burgoyne et al. (2014)]. The software is available at [https://bitbucket.org/jaburgoyne/mirexace BitBucket]. It uses the detailed results provided below as input.

==Submissions==

{| class="wikitable"
!
! Abstract
! Contributors
|-
| HL2
| style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2020/HL2.pdf PDF]
| [http://mirlag.org Yuan-Hao Ku], [http://mirlag.org Hsueh-Han Lee]
|}

==Results==

===Summary===

All figures can be interpreted as percentages and range from 0 (worst) to 100 (best).

=====Isophonics2009=====
<csv>2020/ace/2020-Isophonics2009.csv</csv>
=====Billboard2012=====
<csv>2020/ace/2020-Billboard2012.csv</csv>
=====Billboard2013=====
<csv>2020/ace/2020-Billboard2013.csv</csv>
=====JayChou29=====
<csv>2020/ace/2020-JayChou29.csv</csv>
=====RobbieWilliams=====
<csv>2020/ace/2020-RobbieWilliams.csv</csv>
=====RWC-Popular=====
<csv>2020/ace/2020-RWC-Popular.csv</csv>
=====USPOP2002Chords=====
<csv>2020/ace/2020-USPOP2002Chords.csv</csv>
=====CASD-Annotator1=====
<csv>2020/ace/2020-CASD-Annotator1.csv</csv>
=====CASD-Annotator2=====
<csv>2020/ace/2020-CASD-Annotator2.csv</csv>
=====CASD-Annotator3=====
<csv>2020/ace/2020-CASD-Annotator3.csv</csv>
=====CASD-Annotator4=====
<csv>2020/ace/2020-CASD-Annotator4.csv</csv>



===Detailed Results===

More details about the performance of the algorithms, including per-song performance and supplementary statistics, are available from [https://github.com/ismir-mirex/ace-results/tree/master/2020 this repository].
.

===Algorithmic Output===

The raw output of the algorithms are available in [https://github.com/ismir-mirex/ace-output/tree/master/2019 this repository]. They can be used to experiment with alternative evaluation measures and statistics.

2020:Audio Chord Estimation Results

2020-10-14T19:23:57Z

Yun Hao: Created page with "==Introduction== This page contains the results of the 2020 edition of the MIREX automatic chord estimation tasks. This edition was the eighth one since the reorganization of..."

==Introduction==

This page contains the results of the 2020 edition of the MIREX automatic chord estimation tasks. This edition was the eighth one since the reorganization of the evaluation procedure in 2013. The results can therefore be directly compared to those of the last six years. Chord labels are evaluated according to five different chord vocabularies and the segmentation is also assessed. Additional information about the used measures can be found on the page of the [[2013:Audio_Chord_Estimation_Results_MIREX_2009 | 2013 edition]].

==What’s new?==
* All datasets and evaluation procedures are the same as last year's MIREX.

==Software==
All software used for the evaluation has been made open-source. The evaluation framework is described by [http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6637748 Pauwels and Peeters (2013)]. The corresponding binaries and code repository can be found on [https://github.com/jpauwels/MusOOEvaluator GitHub] and the used measures are available as presets. The raw algorithmic output provided below makes it possible to calculate the additional measures from the paper (separate results for tetrads, etc.), in addition to those presented below. More help can be found in the [https://github.com/jpauwels/MusOOEvaluator/blob/master/README.md readme].

The statistical comparison between the different submissions is explained in [http://www.terasoft.com.tw/conf/ismir2014/proceedings/T095_250_Paper.pdf Burgoyne et al. (2014)]. The software is available at [https://bitbucket.org/jaburgoyne/mirexace BitBucket]. It uses the detailed results provided below as input.

==Submissions==

{| class="wikitable"
!
! Abstract
! Contributors
|-
| HL2
| style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2020/HL2.pdf PDF]
| [http://mirlag.org Yuan-Hao Ku], [http://mirlag.org Hsueh-Han Lee]
|}

==Results==

===Summary===

All figures can be interpreted as percentages and range from 0 (worst) to 100 (best).

=====Isophonics2009=====
<csv>2020/ace/2020-Isophonics2009.csv</csv>
=====Billboard2012=====
<csv>2020/ace/2020-Billboard2012.csv</csv>
=====Billboard2013=====
<csv>2020/ace/2020-Billboard2013.csv</csv>
=====JayChou29=====
<csv>2020/ace/2020-JayChou29.csv</csv>
=====RobbieWilliams=====
<csv>2020/ace/2020-RobbieWilliams.csv</csv>
=====RWC-Popular=====
<csv>2020/ace/2020-RWC-Popular.csv</csv>
=====USPOP2002Chords=====
<csv>2020/ace/2020-USPOP2002Chords.csv</csv>
=====CASD-Annotator1=====
<csv>2020/ace/2020-CASD-Annotator1.csv</csv>
=====CASD-Annotator2=====
<csv>2020/ace/2020-CASD-Annotator2.csv</csv>
=====CASD-Annotator3=====
<csv>2020/ace/2020-CASD-Annotator3.csv</csv>
=====CASD-Annotator4=====
<csv>2020/ace/2020-CASD-Annotator4.csv</csv>



===Detailed Results===

More details about the performance of the algorithms, including per-song performance and supplementary statistics, are available from [https://github.com/ismir-mirex/ace-results/tree/master/2019 this repository].
.

===Algorithmic Output===

The raw output of the algorithms are available in [https://github.com/ismir-mirex/ace-output/tree/master/2019 this repository]. They can be used to experiment with alternative evaluation measures and statistics.

2020:Audio Key Detection Results

2020-10-14T19:13:57Z

Yun Hao: Created page with "==Introduction== This page contains the results of the 2020 edition of the MIREX automatic key detection estimation task. ==What’s new?== * Nothing has changed, which mean..."

==Introduction==

This page contains the results of the 2020 edition of the MIREX automatic key detection estimation task.

==What’s new?==
* Nothing has changed, which means the results can be directly compared to last year's.

==Submissions==

{| class="wikitable"
!
! Abstract
! Contributors
|-
| CG1
| style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2020/CG1.pdf PDF]
| [http://www.uab.cat David Castells-Rufas], [http://www.uab.cat/enginyeria/ Adria Galin]
|-
| CG2
| style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2020/CG2.pdf PDF]
| [http://www.uab.cat David Castells-Rufas], [http://www.uab.cat/enginyeria/ Adria Galin]
|-
| DX1
| style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2020/DX1.pdf PDF]
| [https://y.music.163.com/m/ Yang Deng], [https://github.com/xuziyao26 Ziyao Xu]
|-
| YD1
| style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2020/YD1.pdf PDF]
| [https://y.music.163.com/m/ Yang Deng], [https://github.com/xuziyao26 Ziyao Xu]
|}

==Results==

All figures can be interpreted as percentages and range from 0 (worst) to 100 (best).

====MIREX2005Key====
<csv>2020/akd/2020-MIREX2005Key.csv</csv>

====GiantStepsKey====
<csv>2020/akd/2020-GiantStepsKey.csv</csv>
====PresegmentedKeyIsophonics====
<csv>2020/akd/2020-PresegmentedKeyIsophonics.csv</csv>
====PresegmentedKeyRobbieWilliams====
<csv>2020/akd/2020-PresegmentedKeyRobbieWilliams.csv</csv>
====Billboard2012Key====
<csv>2020/akd/2020-Billboard2012Key.csv</csv>

2020:MIREX2020 Results

2020-10-14T18:35:58Z

Yun Hao: /* Results by Task (More results are coming) */

2020:MIREX2020 Results

2020-10-13T18:23:10Z

Yun Hao: /* Results by Task (More results are coming) */

2020:MIREX2020 Results

2020-10-12T23:02:37Z

Yun Hao: /* Results by Task (More results are coming) */

2020:MIREX2020 Results

2020-10-12T19:01:41Z

Yun Hao: /* Results by Task (More results are coming) */

2019:MIREX2019 Results

2020-10-12T19:00:55Z

Yun Hao: /* Results by Task (More results are coming) */

==Overall Results Poster==
Coming soon

==Results by Task (More results are coming) ==
* Multiple Fundamental Frequency Estimation & Tracking Results
** [[2019:Multiple_Fundamental_Frequency_Estimation_%26_Tracking_Results_%2D_MIREX_Dataset | MIREX Dataset]]  
** [[2019:Multiple_Fundamental_Frequency_Estimation_%26_Tracking_Results_%2D_Su_Dataset | Su Dataset]]  
* [https://www.music-ir.org/mirex/wiki/2019:Music_Detection_Results Music Detection Results]  
* [https://www.music-ir.org/mirex/wiki/2019:Patterns_for_Prediction_Results Patterns for Prediction Results]  
* Audio Melody Extraction Results
** [https://nema.lis.illinois.edu/nema_out/mirex2019/results/ame/adc04/ ADC04 Dataset]  
** [https://nema.lis.illinois.edu/nema_out/mirex2019/results/ame/mrx05/ MIREX05 Dataset]  
** [https://nema.lis.illinois.edu/nema_out/mirex2019/results/ame/ind08/ INDIAN08 Dataset]  
** [https://nema.lis.illinois.edu/nema_out/mirex2019/results/ame/mrx09_0db/ MIREX09 0dB Dataset]  
** [https://nema.lis.illinois.edu/nema_out/mirex2019/results/ame/mrx09_m5db/ MIREX09 -5dB Dataset]  
** [https://nema.lis.illinois.edu/nema_out/mirex2019/results/ame/mrx09_p5db/ MIREX09 +5dB Dataset]  
** [https://nema.lis.illinois.edu/nema_out/mirex2019/results/ame/orchset/ ORCHSET15 Dataset]  
* [[2019:Automatic Lyrics-to-Audio Alignment Results | Automatic Lyrics-to-Audio Alignment Results]]  
* [[2019:Drum_Transcription_Results | Drum Transcription]]  
* [[2019:Audio Fingerprinting Results|Audio Fingerprinting Results]]
* [[2019:Audio_Key_Detection_Results | Audio Key Detection]]  
* [[2019:Audio_Chord_Estimation_Results | Audio Chord Estimation]]
** [[2019:Audio_Chord_Estimation_Results#Isophonics2009 | Isophonics2009 Dataset]]  
** [[2019:Audio_Chord_Estimation_Results#Billboard2012 | Billboard2012 Dataset]]  
** [[2019:Audio_Chord_Estimation_Results#Billboard_013 | Billboard2013 Dataset]]  
** [[2019:Audio_Chord_Estimation_Results#JayChou29 | JayChou29 Dataset]]  
** [[2019:Audio_Chord_Estimation_Results#RobbieWilliams | RobbieWilliams Dataset]]  
** [[2019:Audio_Chord_Estimation_Results#RWC-Popular | RWC-Popular Dataset]]  
** [[2019:Audio_Chord_Estimation_Results#USPOP2002Chords | USPOP2002Chords Dataset]]  
*Train-Test Task Set
** [https://www.music-ir.org/nema_out/mirex2019/results/act/composer_report/ Audio Classical Composer Identification Results ]  
** [https://www.music-ir.org/nema_out/mirex2019/results/act/latin_report/ Audio Latin Genre Classification Results ]  
** [https://www.music-ir.org/nema_out/mirex2019/results/act/mood_report/index.html Audio Music Mood Classification Results ]  
** [https://www.music-ir.org/nema_out/mirex2019/results/act/mixed_report/ Audio Mixed Popular Genre Classification Results ]  
** [https://www.music-ir.org/nema_out/mirex2019/results/act/kgenrek_report/ Audio KPOP Genre (Annotated by Korean Annotators) Classification Results ]  
** [https://www.music-ir.org/nema_out/mirex2019/results/act/kgenrea_report/ Audio KPOP Genre (Annotated by American Annotators) Classification Results ]  
** [https://www.music-ir.org/nema_out/mirex2019/results/act/kmoodk_report/ Audio KPOP Mood (Annotated by Korean Annotators) Classification Results ]  
** [https://www.music-ir.org/nema_out/mirex2019/results/act/kmooda_report/ Audio KPOP Mood (Annotated by American Annotators) Classification Results ]  

* Audio Beat Tracking Results
** [https://nema.lis.illinois.edu/nema_out/mirex2019/results/abt/smc/ SMC Dataset]  
** [https://nema.lis.illinois.edu/nema_out/mirex2019/results/abt/maz/ MAZ Dataset]  

* [[2019:Audio Cover Song Identification Results|Audio Cover Song Identification Results]]

2019:Audio Cover Song Identification Results

2020-10-12T19:00:00Z

Yun Hao: /* General Legend */

== Introduction ==

Audio Cover Song (ACS) Identification was evaluated against two datasets: ''Mixed Collection'' and ''Sapp's Mazurka Collection''.

===Mixed Collection Information===
This is the "original" ACS collection. Within the 1000 pieces in the Audio Cover Song database, there are embedded 30 different "cover songs" each represented by 11 different "versions" for a total of 330 audio files (16bit, monophonic, 22.05khz, wav). The "cover songs" represent a variety of genres (e.g., classical, jazz, gospel, rock, folk-rock, etc.) and the variations span a variety of styles and orchestrations.

Using each of these cover song files in turn as the "seed/query" file, we will examine the returned lists of items for the presence of the other 10 versions of the "seed/query" file.

===Sapp's Mazurka Collection Information ===
In addition to our original ACS dataset, we used the [http://www.mazurka.org.uk/ Mazurka.org dataset] put together by Craig Sapp. We randomly chose 11 versions from 49 mazurkas and ran it as a separate ACS subtask. Systems returned a distance matrix of 539x539 from which we located the ranks of each of the associated cover versions.

== General Legend ==
{| border="1" cellspacing="0" style="text-align: left; width: 800px;"
|- style="background: yellow;"
! width="80" | Sub code
! width="200" | Submission name
! width="80" style="text-align: center;" | Abstract
! width="440" | Contributors
|-
! CH1
| CH1 || style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2019/CH1.pdf PDF] || [http://cise.ecust.edu.cn/ Ning Chen], [http://www.ecust.edu.cn/ Jingyi Hu]
|-
! CZWZ1
| CSI_DL || style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2019/JS2.pdf PDF] ||[https://sites.google.com/site/weiqzhang/ Zimo Cheng], [http://sites.google.com/site/weiqzhang/ Junfan Zhao], [https://sites.google.com/site/weiqzhang/ Guanbo Wang], [http://www.tsinghua.edu.cn/ Wei-Qiang Zhang]
|-
! JS1
| JS1 || style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2019/JS1.pdf PDF] ||[https://sites.google.com/site/jinseo/home Jin Soo Seo]
|-
! JS2
| JS2 || style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2019/JS2.pdf PDF] ||[https://sites.google.com/site/jinseo/home Jin Soo Seo]
|-
! YWJ2
| ywj_CSIp || style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2019/YWJ2.pdf PDF] ||[http://slam.iis.sinica.edu.tw/index.htm Ming-Chi Yen], [http://www.iis.sinica.edu.tw Hsin-Min Wang], [http://mirlab.org/jang Jyh-Shing Roger Jang]
|-
! YXCY1
| CQTNet || style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2019/YXCY1.pdf PDF] ||[http://www.icst.pku.edu.cn Zhesong Yu], [http://www.icst.pku.edu.cn Xiaoshuo Xu], [http://www.icst.pku.edu.cn/team/content_266.htm Xiaoou Chen], [http://www.icst.pku.edu.cn/ Deshun Yang]
|-
|}

== Results ==

===Mixed Collection===

====Summary Results====
<csv p=2>2019/acs/coversong1000.summary.csv</csv>

====Number of Correct Covers at Rank X Returned in Top Ten====
<csv>2019/acs/coversong1000.toptendist.csv</csv>

====Average Performance per Query Group====
<csv p=2>2019/acs/coversong1000.precision.groups.csv</csv>

===Sapp's Mazuraka Collection===

====Summary results====
<csv p=2>2019/acs/mazurkas.summary.csv</csv>

====Number of Correct Covers at Rank X Returned in Top Ten====
<csv>2019/acs/mazurkas.toptendist.csv</csv>

====Average Performance per Query Group====
<csv p=2>2019/acs/mazurkas.precision.groups.csv</csv>

==Individual Results Files==

===Mixed Collection===
'''Average Precision by Query'''

'''CH1''' : [https://music-ir.org/mirex/results/2019/acs/CH1.coversong1000.avgprec.txt Ning Chen, Jingyi Hu] 
'''CZWZ1''' : [https://music-ir.org/mirex/results/2019/acs/CZWZ1.coversong1000.avgprec.txt Zimo Cheng, Junfan Zhao, Guanbo Wang, Wei-Qiang Zhang] 
'''JS1''' : [https://music-ir.org/mirex/results/2019/acs/JS1.coversong1000.avgprec.txt Jin Soo Seo]
'''JS2''' : [https://music-ir.org/mirex/results/2019/acs/JS2.coversong1000.avgprec.txt Jin Soo Seo]
'''YWJ2''' : [https://music-ir.org/mirex/results/2019/acs/YWJ2.coversong1000.avgprec.txt Ming-Chi Yen, Hsin-Min Wang, Jyh-Shing Roger Jang]
'''YXCY1''' : [https://music-ir.org/mirex/results/2019/acs/YXCY1.coversong1000.avgprec.txt Zhesong Yu, Xiaoshuo Xu, Xiaoou Chen, Deshun Yang]

'''Rank Lists'''

'''CH1''' : [https://music-ir.org/mirex/results/2019/acs/CH1.coversong1000.ranklist.txt Ning Chen, Jingyi Hu] 
'''CZWZ1''' : [https://music-ir.org/mirex/results/2019/acs/CZWZ1.coversong1000.ranklist.txt Zimo Cheng, Junfan Zhao, Guanbo Wang, Wei-Qiang Zhang] 
'''JS1''' : [https://music-ir.org/mirex/results/2019/acs/JS1.coversong1000.ranklist.txt Jin Soo Seo]
'''JS2''' : [https://music-ir.org/mirex/results/2019/acs/JS2.coversong1000.ranklist.txt Jin Soo Seo]
'''YWJ2''' : [https://music-ir.org/mirex/results/2019/acs/YWJ2.coversong1000.ranklist.txt Ming-Chi Yen, Hsin-Min Wang, Jyh-Shing Roger Jang]
'''YXCY1''' : [https://music-ir.org/mirex/results/2019/acs/YXCY1.coversong1000.ranklist.txt Zhesong Yu, Xiaoshuo Xu, Xiaoou Chen, Deshun Yang]

===Mazurkas===
'''Average Precision by Query'''

'''CH1''' : [https://music-ir.org/mirex/results/2019/acs/CH1.mazurkas.avgprec.txt Ning Chen, Jingyi Hu] 
'''CZWZ1''' : [https://music-ir.org/mirex/results/2019/acs/CZWZ1.mazurkas.avgprec.txt Zimo Cheng, Junfan Zhao, Guanbo Wang, Wei-Qiang Zhang] 
'''JS1''' : [https://music-ir.org/mirex/results/2019/acs/JS1.mazurkas.avgprec.txt Jin Soo Seo]
'''JS2''' : [https://music-ir.org/mirex/results/2019/acs/JS2.mazurkas.avgprec.txt Jin Soo Seo]
'''YWJ2''' : [https://music-ir.org/mirex/results/2019/acs/YWJ2.mazurkas.avgprec.txt Ming-Chi Yen, Hsin-Min Wang, Jyh-Shing Roger Jang]
'''YXCY1''' : [https://music-ir.org/mirex/results/2019/acs/YXCY1.mazurkas.avgprec.txt Zhesong Yu, Xiaoshuo Xu, Xiaoou Chen, Deshun Yang]

'''Rank Lists'''

'''CH1''' : [https://music-ir.org/mirex/results/2019/acs/CH1.mazurkas.ranklist.txt Ning Chen, Jingyi Hu] 
'''CZWZ1''' : [https://music-ir.org/mirex/results/2019/acs/CZWZ1.mazurkas.ranklist.txt Zimo Cheng, Junfan Zhao, Guanbo Wang, Wei-Qiang Zhang] 
'''JS1''' : [https://music-ir.org/mirex/results/2019/acs/JS1.mazurkas.ranklist.txt Jin Soo Seo]
'''JS2''' : [https://music-ir.org/mirex/results/2019/acs/JS2.mazurkas.ranklist.txt Jin Soo Seo]
'''YWJ2''' : [https://music-ir.org/mirex/results/2019/acs/YWJ2.mazurkas.ranklist.txt Ming-Chi Yen, Hsin-Min Wang, Jyh-Shing Roger Jang]
'''YXCY1''' : [https://music-ir.org/mirex/results/2019/acs/YXCY1.mazurkas.ranklist.txt Zhesong Yu, Xiaoshuo Xu, Xiaoou Chen, Deshun Yang]

2020:Audio Cover Song Identification Results

2020-10-12T18:43:45Z

Yun Hao: Created page with "== Introduction == Audio Cover Song (ACS) Identification was evaluated against two datasets: ''Mixed Collection'' and ''Sapp's Mazurka Collection''. ===Mixed Collection Info..."

== Introduction ==

Audio Cover Song (ACS) Identification was evaluated against two datasets: ''Mixed Collection'' and ''Sapp's Mazurka Collection''.

===Mixed Collection Information===
This is the "original" ACS collection. Within the 1000 pieces in the Audio Cover Song database, there are embedded 30 different "cover songs" each represented by 11 different "versions" for a total of 330 audio files (16bit, monophonic, 22.05khz, wav). The "cover songs" represent a variety of genres (e.g., classical, jazz, gospel, rock, folk-rock, etc.) and the variations span a variety of styles and orchestrations.

Using each of these cover song files in turn as the "seed/query" file, we will examine the returned lists of items for the presence of the other 10 versions of the "seed/query" file.

===Sapp's Mazurka Collection Information ===
In addition to our original ACS dataset, we used the [http://www.mazurka.org.uk/ Mazurka.org dataset] put together by Craig Sapp. We randomly chose 11 versions from 49 mazurkas and ran it as a separate ACS subtask. Systems returned a distance matrix of 539x539 from which we located the ranks of each of the associated cover versions.

== General Legend ==
{| border="1" cellspacing="0" style="text-align: left; width: 800px;"
|- style="background: yellow;"
! width="80" | Sub code
! width="200" | Submission name
! width="80" style="text-align: center;" | Abstract
! width="440" | Contributors
|-
! DY1
| SinoNet || style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2020/DY1.pdf PDF] || [https://github.com/diggerdu Xingjian Du], [http://www.icst.pku.edu.cn Zhesong Yu]
|-
! DYZC1
| CasperNet0 || style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2020/DYZC1.pdf PDF] || [https://github.com/diggerdu Xingjian Du], [http://www.icst.pku.edu.cn Zhesong Yu],, [http://www.tencent.com/en-us/index.shtml Bilei Zhu], [http://www.icst.pku.edu.cn/team/content_266.htm Xiaoou Chen]
|-
! HCCL1
| CSI task based on Subspace Merging of Enhanced Cross-Similarity Graphs || style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2020/HCCL1.pdf PDF] ||[http://cise.ecust.edu.cn/ Jingyi Hu], [http://cise.ecust.edu.cn/ Ning Chen],[http://www.ecust.edu.cn/ Jialing Cao], [http://www.ecust.edu.cn/ Han Lei]
|-
! ZL1
| ZJ_T1 || style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2020/ZL1.pdf PDF] || [http://ir.netease.com/index.php/ Jian Zhao ], [http://163.com Huaping Liu]
|}

== Results ==

===Mixed Collection===

====Summary Results====
<csv p=2>2020/acs/coversong1000.summary.csv</csv>

====Number of Correct Covers at Rank X Returned in Top Ten====
<csv>2020/acs/coversong1000.toptendist.csv</csv>

====Average Performance per Query Group====
<csv p=2>2020/acs/coversong1000.precision.groups.csv</csv>

===Sapp's Mazuraka Collection===

====Summary results====
<csv p=2>2020/acs/mazurkas.summary.csv</csv>

====Number of Correct Covers at Rank X Returned in Top Ten====
<csv>2020/acs/mazurkas.toptendist.csv</csv>

====Average Performance per Query Group====
<csv p=2>2020/acs/mazurkas.precision.groups.csv</csv>

==Individual Results Files==

===Mixed Collection===
'''Average Precision by Query'''

'''DY1''' : [https://music-ir.org/mirex/results/2020/acs/DY1.coversong1000.avgprec.txt Xingjian Du, Zhesong Yu] 
'''DYZC1''' : [https://music-ir.org/mirex/results/2020/acs/DYZC1.coversong1000.avgprec.txt Xingjian Du, Zhesong Yu,, Bilei Zhu, Xiaoou Chen] 

'''ZL1''' : [https://music-ir.org/mirex/results/2020/acs/ZL1.coversong1000.avgprec.txt Jian Zhao, Huaping Liu] 

'''Rank Lists'''

'''DY1''' : [https://music-ir.org/mirex/results/2020/acs/DY1.coversong1000.ranklist.txt Xingjian Du, Zhesong Yu] 
'''DYZC1''' : [https://music-ir.org/mirex/results/2020/acs/DYZC1.coversong1000.ranklist.txt Xingjian Du, Zhesong Yu,, Bilei Zhu, Xiaoou Chen] 

'''ZL1''' : [https://music-ir.org/mirex/results/2020/acs/ZL1.coversong1000.ranklist.txt Jian Zhao, Huaping Liu] 

===Mazurkas===
'''Average Precision by Query'''
'''DY1''' : [https://music-ir.org/mirex/results/2020/acs/DY1.mazurkas.avgprec.txt Xingjian Du, Zhesong Yu] 
'''DYZC1''' : [https://music-ir.org/mirex/results/2020/acs/DYZC1.mazurkas.avgprec.txt Xingjian Du, Zhesong Yu,, Bilei Zhu, Xiaoou Chen] 
'''HCCL1''' : [https://music-ir.org/mirex/results/2020/acs/HCCL1.mazurkas.avgprec.txt Jingyi Hu, Ning Chen,Jialing Cao, Han Lei] 
'''ZL1''' : [https://music-ir.org/mirex/results/2020/acs/ZL1.mazurkas.avgprec.txt Jian Zhao, Huaping Liu] 

'''Rank Lists'''
'''DY1''' : [https://music-ir.org/mirex/results/2020/acs/DY1.mazurkas.ranklist.txt Xingjian Du, Zhesong Yu] 
'''DYZC1''' : [https://music-ir.org/mirex/results/2020/acs/DYZC1.mazurkas.ranklist.txt Xingjian Du, Zhesong Yu,, Bilei Zhu, Xiaoou Chen] 
'''HCCL1''' : [https://music-ir.org/mirex/results/2020/acs/HCCL1.mazurkas.ranklist.txt Jingyi Hu, Ning Chen,Jialing Cao, Han Lei] 
'''ZL1''' : [https://music-ir.org/mirex/results/2020/acs/ZL1.mazurkas.ranklist.txt Jian Zhao, Huaping Liu]

2019:Multiple Fundamental Frequency Estimation & Tracking Results - MIREX Dataset

2020-10-09T18:29:11Z

Yun Hao: /* General Legend */

==Introduction==
These are the results for the 2018 running of the Multiple Fundamental Frequency Estimation and Tracking task on MIREX dataset. For background information about this task set please refer to the [[2019:Multiple Fundamental Frequency Estimation & Tracking]] page.

==General Legend==
{| border="1" cellspacing="0" style="text-align: left; width: 800px;"
|- style="background: yellow;"
! width="80" | Sub code
! width="200" | Submission name
! width="80" style="text-align: center;" | Abstract
! width="440" | Contributors
|-
! AR2
| qhear || style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2019/AR2.pdf PDF] || [https://github.com/antonrunov Anton Runov]
|-
! BK1 (piano subtask)
| PianoTranscriptor.2019 || style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2019/BK1.pdf PDF] || [http://www.ofai.at Sebastian Böck], [http://www.cp.jku.at Rainer Kelz]
|-
! CB1
| Silvet || style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2019/CB1.pdf PDF] || [https://code.soundsoftware.ac.uk/users/3 Chris Cannam], [http://www.eecs.qmul.ac.uk/~emmanouilb/ Emmanouil Benetos]
|-
! CB2
| Silvet Live || style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2019/CB2.pdf PDF] || [https://code.soundsoftware.ac.uk/users/3 Chris Cannam], [http://www.eecs.qmul.ac.uk/~emmanouilb/ Emmanouil Benetos]
|-
! HH2 (task1)
| mffet v.1 || style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2019/HH2.pdf PDF] || [http://mirlab.org/users/hsiangyu.huang/ Huang Hsiang-Yu]
|-
! KN3 (piano subtask)
| AR_BEAM || style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2019/KN3.pdf PDF] || [http://mac.kaist.ac.kr/ Taegyun Kwon], [http://ccrma.stanford.edu/~juhan Juhan Nam], [http://mac.kaist.ac.kr/ Dasaem Jung]
|-
! KNJ1 (piano subtask)
| AR_SIMPLE || style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2019/KNJ1.pdf PDF] || [http://mac.kaist.ac.kr/ Taegyun Kwon], [http://ccrma.stanford.edu/~juhan Juhan Nam], [http://mac.kaist.ac.kr/ Dasaem Jung]
|-
! KY1 (task2)
| MetaAI_Ensemble_SingleDomain || style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2019/KY_YK.pdf PDF] || [https://www.sktelecom.com/index_en.html Changhyun Kim], [https://www.sktelecom.com/index_en.html Sangeon Yong]
|-
! KY2 (task2)
| MetaAI_SingleModel_MultiDomain || style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2019/KY_YK.pdf PDF] || [https://www.sktelecom.com/index_en.html Changhyun Kim], [https://www.sktelecom.com/index_en.html Sangeon Yong]
|-
! SBJ1-4 (task1)
| SBJ1-4 || style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2019/SBJ1.pdf PDF] || [https://tu-dresden.de/ing/elektrotechnik/ias/juniorprofessur-fuer-kognitive-systeme?set_language=en Peter Steiner], [https://tu-dresden.de/ing/elektrotechnik/ias/juniorprofessur-fuer-kognitive-systeme?set_language=en Peter Birkholz], [https://telefoonboek.ugent.be/en/people/802000630839 Azarakhsh Jalalvand]
|-
! YK1 (task2)
| MetaAI_Ensemble_SingleDomain || style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2019/KY_YK.pdf PDF] || [https://www.sktelecom.com/index_en.html Sangeon Yong], [https://www.sktelecom.com/index_en.html Changhyun Kim]
|-
! YK2 (task2)
| MetaAI_SingleModel_SingleDomain || style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2019/KY_YK.pdf PDF] || [https://www.sktelecom.com/index_en.html Sangeon Yong], [https://www.sktelecom.com/index_en.html Changhyun Kim]
|-
|}

==Task 1: Multiple Fundamental Frequency Estimation (MF0E)==

===MF0E Overall Summary Results===
Below are the average scores across 40 test files. These files come from 3 different sources: woodwind quintet recording of bassoon, clarinet, horn,flute and oboe (UIUC); Rendered MIDI using RWC database donated by IRCAM and a quartet recording of bassoon, clarinet, violin and sax donated by Dr. Bryan Pardo`s Interactive Audio Lab (IAL). 20 files coming from 5 sections of the woodwind recording where each section has 4 files ranging from 2 polyphony to 5 polyphony. 12 files from IAL, coming from 4 different songs ranging from 2 polyphony to 4 polyphony and 8 files from RWC synthesized midi ranging from 2 different songs ranging from 2 polphony to 5 polyphony.

====Detailed Results====

<csv>2019/mf0/est_mirex/summary/task1.results.csv</csv>

====Detailed Chroma Results====
Here, accuracy is assessed on chroma results (i.e. all F0's are mapped to a single octave before evaluating)

<csv>2019/mf0/est_mirex/summary/task1.chroma.results.csv</csv>

===Individual Results Files for Task 1===
'''AR2'''= [https://music-ir.org/mirex/results/2019/mf0/est_mirex/AR2.tar.gz Anton Runov] 
'''CB1'''= [https://music-ir.org/mirex/results/2019/mf0/est_mirex/CB1.tar.gz Chris Cannam, Emmanouil Benetos] 
'''CB2'''= [https://music-ir.org/mirex/results/2019/mf0/est_mirex/CB2.tar.gz Chris Cannam, Emmanouil Benetos] 
'''HH2'''= [https://music-ir.org/mirex/results/2019/mf0/est_mirex/HH2.tar.gz Huang Hsiang-Yu] 
'''SBJ1'''= [https://music-ir.org/mirex/results/2019/mf0/est_mirex/SBJ1.tar.gz Peter Steiner, Peter Birkholz, Azarakhsh Jalalvand] 
'''SBJ2'''= [https://music-ir.org/mirex/results/2019/mf0/est_mirex/SBJ2.tar.gz Peter Steiner, Peter Birkholz, Azarakhsh Jalalvand] 
'''SBJ3'''= [https://music-ir.org/mirex/results/2019/mf0/est_mirex/SBJ3.tar.gz Peter Steiner, Peter Birkholz, Azarakhsh Jalalvand] 
'''SBJ4'''= [https://music-ir.org/mirex/results/2019/mf0/est_mirex/SBJ4.tar.gz Peter Steiner, Peter Birkholz, Azarakhsh Jalalvand] 

=====Info about the filenames=====
The filenames starting with part* comes from acoustic woodwind recording, the ones starting with RWC are synthesized. The legend about the instruments are:

'''bs''' = bassoon,
'''cl''' = clarinet,
'''fl''' = flute,
'''hn''' = horn,
'''ob''' = oboe,
'''vl''' = violin,
'''cel''' = cello,
'''gtr''' = guitar,
'''sax''' = saxophone,
'''bass''' = electric bass guitar

===Friedman tests for Multiple Fundamental Frequency Estimation (MF0E)===
The Friedman test was run in MATLAB to test significant differences amongst systems with regard to the performance (accuracy) on individual files.

====Tukey-Kramer HSD Multi-Comparison====

<csv>2019/mf0/est_mirex/summary/Accuracy_Per_Song_Friedman_Mean_Rankstask1.friedman.Friedman_TukeyKramerHSD.csv</csv>

[[File:2019_Accuracy_Per_Song_Friedman_Mean_Rankstask1.friedman.Friedman_Mean_Ranks.png|500px]]

==Task 2:Note Tracking (NT)==
===NT Mixed Set Overall Summary Results===
This subtask is evaluated in two different ways. In the first setup , a returned note is assumed correct if its onset is within +-50ms of a ref note and its F0 is within +- quarter tone of the corresponding reference note, ignoring the returned offset values. In the second setup, on top of the above requirements, a correct returned note is required to have an offset value within 20% of the ref notes duration around the ref note`s offset, or within 50ms whichever is larger.

A total of 34 files were used in this subtask: 16 from woodwind recording, 8 from IAL quintet recording and 6 piano.

<csv>2019/mf0/nt_mirex/summary/task2.overall.results.csv</csv>

====Detailed Results====

<csv>2019/mf0/nt_mirex/summary/task2.results.csv</csv>

====Detailed Chroma Results====
Here, accuracy is assessed on chroma results (i.e. all F0's are mapped to a single octave before evaluating)

<csv>2019/mf0/nt_mirex/summary/task2.chroma.results.csv</csv>

====Results Based on Onset Only====

<csv>2019/mf0/nt_mirex/summary/task2.onsetOnly.results.csv</csv>

====Chroma Results Based on Onset Only====

<csv>2019/mf0/nt_mirex/summary/task2.onsetOnly.chroma.results.csv</csv>

====Friedman Tests for Note Tracking====
The Friedman test was run in MATLAB to test significant differences amongst systems with regard to the F-measure on individual files.

=====Tukey-Kramer HSD Multi-Comparison for Task2=====

<csv>2019/mf0/nt_mirex/summary/Accuracy_Per_Song_Friedman_Mean_Rankstask2.onsetOnly.friedman.Friedman_TukeyKramerHSD.csv</csv>

[[File:2019_Accuracy_Per_Song_Friedman_Mean_Rankstask2.onsetOnly.friedman.Friedman_Mean_Ranks.png|500px]]

===NT Piano-Only Overall Summary Results===
This subtask is evaluated in two different ways. In the first setup , a returned note is assumed correct if its onset is within +-50ms of a ref note and its F0 is within +- quarter tone of the corresponding reference note, ignoring the returned offset values. In the second setup, on top of the above requirements, a correct returned note is required to have an offset value within 20% of the ref notes duration around the ref note`s offset, or within 50ms whichever is larger.
6 piano recordings are evaluated separately for this subtask.

<csv>2019/mf0/nt_mirex/summary_piano_subtask/task2_piano.overall.results.csv</csv>

====Detailed Results====

<csv>2019/mf0/nt_mirex/summary_piano_subtask/task2_piano.results.csv</csv>

====Detailed Chroma Results====
Here, accuracy is assessed on chroma results (i.e. all F0's are mapped to a single octave before evaluating)

<csv>2019/mf0/nt_mirex/summary_piano_subtask/task2_piano.chroma.results.csv</csv>

====Results Based on Onset Only====

<csv>2019/mf0/nt_mirex/summary_piano_subtask/task2_piano.onsetOnly.results.csv</csv>

====Chroma Results Based on Onset Only====

<csv>2019/mf0/nt_mirex/summary_piano_subtask/task2_piano.onsetOnly.chroma.results.csv</csv>

===Individual Results Files for Task 2===
'''AR2'''= [https://music-ir.org/mirex/results/2019/mf0/nt_mirex/AR2.tar.gz Anton Runov] 
'''CB1'''= [https://music-ir.org/mirex/results/2019/mf0/nt_mirex/CB1.tar.gz Chris Cannam, Emmanouil Benetos] 
'''CB2'''= [https://music-ir.org/mirex/results/2019/mf0/nt_mirex/CB2.tar.gz Chris Cannam, Emmanouil Benetos] 
'''BK1'''= [https://music-ir.org/mirex/results/2019/mf0/nt_mirex/BK1.tar.gz Sebastian Böck, Rainer Kelz] 
'''KN3'''= [https://music-ir.org/mirex/results/2019/mf0/nt_mirex/KN3.tar.gz Taegyun Kwon, Juhan Nam, Dasaem Jung] 
'''KNJ1'''= [https://music-ir.org/mirex/results/2019/mf0/nt_mirex/KNJ1.tar.gz Taegyun Kwon, Juhan Nam, Dasaem Jung] 
'''KY1'''= [https://music-ir.org/mirex/results/2019/mf0/nt_mirex/KY1.tar.gz Changhyun Kim, Sangeon Yong] 
'''KY2'''= [https://music-ir.org/mirex/results/2019/mf0/nt_mirex/KY2.tar.gz Changhyun Kim, Sangeon Yong] 
'''YK1'''= [https://music-ir.org/mirex/results/2019/mf0/nt_mirex/YK1.tar.gz Sangeon Yong, Changhyun Kim] 
'''YK2'''= [https://music-ir.org/mirex/results/2019/mf0/nt_mirex/YK2.tar.gz Sangeon Yong, Changhyun Kim]

2019:MIREX2019 Results

2020-10-09T06:30:18Z

Yun Hao: /* Results by Task (More results are coming) */

==Overall Results Poster==
Coming soon

==Results by Task (More results are coming) ==
* Multiple Fundamental Frequency Estimation & Tracking Results
** [[2019:Multiple_Fundamental_Frequency_Estimation_%26_Tracking_Results_%2D_MIREX_Dataset | MIREX Dataset]]  
** [[2019:Multiple_Fundamental_Frequency_Estimation_%26_Tracking_Results_%2D_Su_Dataset | Su Dataset]]  
* [https://www.music-ir.org/mirex/wiki/2019:Music_Detection_Results Music Detection Results]  
* [https://www.music-ir.org/mirex/wiki/2019:Patterns_for_Prediction_Results Patterns for Prediction Results]  
* Audio Melody Extraction Results
** [https://nema.lis.illinois.edu/nema_out/mirex2019/results/ame/adc04/ ADC04 Dataset]  
** [https://nema.lis.illinois.edu/nema_out/mirex2019/results/ame/mrx05/ MIREX05 Dataset]  
** [https://nema.lis.illinois.edu/nema_out/mirex2019/results/ame/ind08/ INDIAN08 Dataset]  
** [https://nema.lis.illinois.edu/nema_out/mirex2019/results/ame/mrx09_0db/ MIREX09 0dB Dataset]  
** [https://nema.lis.illinois.edu/nema_out/mirex2019/results/ame/mrx09_m5db/ MIREX09 -5dB Dataset]  
** [https://nema.lis.illinois.edu/nema_out/mirex2019/results/ame/mrx09_p5db/ MIREX09 +5dB Dataset]  
** [https://nema.lis.illinois.edu/nema_out/mirex2019/results/ame/orchset/ ORCHSET15 Dataset]  
* [[2019:Automatic Lyrics-to-Audio Alignment Results | Automatic Lyrics-to-Audio Alignment Results]]  
* [[2019:Drum_Transcription_Results | Drum Transcription]]  
* [[2019:Audio Fingerprinting Results|Audio Fingerprinting Results]]
* [[2019:Audio_Key_Detection_Results | Audio Key Detection]]  
* [[2019:Audio_Chord_Estimation_Results | Audio Chord Estimation]]
** [[2019:Audio_Chord_Estimation_Results#Isophonics2009 | Isophonics2009 Dataset]]  
** [[2019:Audio_Chord_Estimation_Results#Billboard2012 | Billboard2012 Dataset]]  
** [[2019:Audio_Chord_Estimation_Results#Billboard_013 | Billboard2013 Dataset]]  
** [[2019:Audio_Chord_Estimation_Results#JayChou29 | JayChou29 Dataset]]  
** [[2019:Audio_Chord_Estimation_Results#RobbieWilliams | RobbieWilliams Dataset]]  
** [[2019:Audio_Chord_Estimation_Results#RWC-Popular | RWC-Popular Dataset]]  
** [[2019:Audio_Chord_Estimation_Results#USPOP2002Chords | USPOP2002Chords Dataset]]  
*Train-Test Task Set
** [https://www.music-ir.org/nema_out/mirex2019/results/act/composer_report/ Audio Classical Composer Identification Results ]  
** [https://www.music-ir.org/nema_out/mirex2019/results/act/latin_report/ Audio Latin Genre Classification Results ]  
** [https://www.music-ir.org/nema_out/mirex2019/results/act/mood_report/index.html Audio Music Mood Classification Results ]  
** [https://www.music-ir.org/nema_out/mirex2019/results/act/mixed_report/ Audio Mixed Popular Genre Classification Results ]  
** [https://www.music-ir.org/nema_out/mirex2019/results/act/kgenrek_report/ Audio KPOP Genre (Annotated by Korean Annotators) Classification Results ]  
** [https://www.music-ir.org/nema_out/mirex2019/results/act/kgenrea_report/ Audio KPOP Genre (Annotated by American Annotators) Classification Results ]  
** [https://www.music-ir.org/nema_out/mirex2019/results/act/kmoodk_report/ Audio KPOP Mood (Annotated by Korean Annotators) Classification Results ]  
** [https://www.music-ir.org/nema_out/mirex2019/results/act/kmooda_report/ Audio KPOP Mood (Annotated by American Annotators) Classification Results ]  

* Audio Beat Tracking Results
** [https://nema.lis.illinois.edu/nema_out/mirex2019/results/abt/smc/ SMC Dataset]  
** [https://nema.lis.illinois.edu/nema_out/mirex2019/results/abt/maz/ MAZ Dataset]

2019:MIREX2019 Results

2020-10-09T06:28:07Z

Yun Hao: /* Results by Task (More results are coming) */

2020:MIREX2020 Results

2020-09-18T18:59:45Z

Yun Hao: /* Results by Task (More results are coming) */

2020:Audio Fingerprinting Results

2020-09-08T21:22:10Z

Yun Hao: Created page with "== Introduction == These are the results for the 2020 running of the Audio Fingerprinting task. For background information about this task set please refer to the 2020:Audio..."

== Introduction ==
These are the results for the 2020 running of the Audio Fingerprinting task. For background information about this task set please refer to the [[2020:Audio Fingerprinting]] page.

== General Legend ==
{| border="1" cellspacing="0" style="text-align: left; width: 800px;"
|- style="background: yellow"
! width="80" | Sub code
! width="200" | Submission name
! width="80" style="text-align: center;" | Abstract
! width="540" | Contributors
|-
! LPL1
| NTES_MUSIC_A || style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2020/LPL1.pdf PDF] || Huaping Liu, [http://ir.netease.com/phoenix.zhtml?c=122303&p=irol-IRHome Peng Li], [http://ir.netease.com/phoenix.zhtml?c=122303&p=irol-IRHome Songsheng Pan]
|-
! LPL2
| NTES_MUSIC_B || style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2020/LPL2.pdf PDF] || Huaping Liu, [http://ir.netease.com/phoenix.zhtml?c=122303&p=irol-IRHome Peng Li], [http://ir.netease.com/phoenix.zhtml?c=122303&p=irol-IRHome Songsheng Pan]
|-
! LPL3
| NTES_MUSIC_C || style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2020/LPL3.pdf PDF] || Huaping Liu, [http://ir.netease.com/phoenix.zhtml?c=122303&p=irol-IRHome Peng Li], [http://ir.netease.com/phoenix.zhtml?c=122303&p=irol-IRHome Songsheng Pan]
|-
! LPL4
| NTES_MUSIC_D || style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2020/LPL4.pdf PDF] || Huaping Liu, [http://ir.netease.com/phoenix.zhtml?c=122303&p=irol-IRHome Peng Li], [http://ir.netease.com/phoenix.zhtml?c=122303&p=irol-IRHome Songsheng Pan]
|-
! XXZC1-3
| KUGOU || style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2020/XXZC.pdf PDF] || Chaogang Zhang, ChuanYi Chen, Xiaoguang Xuan, Chunzhi Xiao
|-
|}

==Summary Results==

Size of database and running time are announced together with top-1 hit rate in the following table. Note that running time is announced for reference because machine spec, machine status, and number of cores used by a submission are different. IDs and specs of machines are:

* A and B: 1.9 GHz, 24 cores CPU, 64 GB RAM
* C: a VM with 8 cores CPU and 32 GB RAM, hosted on 2.4 GHz, 32 cores CPU and 128 GB RAM
* D: 2.1 GHz, 24 cores CPU, 32 GB RAM

<csv>2020/afp/result_2020.csv</csv>

2020:MIREX2020 Results

2020-09-08T21:03:43Z

Yun Hao: Created page with "==Results by Task (More results are coming) == * Audio Fingerprinting Results"

==Results by Task (More results are coming) ==
* [[2020:Audio Fingerprinting Results|Audio Fingerprinting Results]]

MediaWiki:Sidebar

2020-09-08T21:03:02Z

Yun Hao:

MIREX HOME

2020-08-31T23:47:08Z

Yun Hao: /* Mailing List Participation */

==Welcome to MIREX 2020==

This is the main page for the 16th running of the Music Information Retrieval Evaluation eXchange (MIREX 2020). The International Music Information Retrieval Systems Evaluation Laboratory (IMIRSEL) at [https://ischool.illinois.edu School of Information Sciences], University of Illinois at Urbana-Champaign ([https://illinois.edu UIUC]) is the principal organizer of MIREX 2020.

The MIREX 2020 community will hold its annual meeting as part of [https://ismir.github.io/ISMIR2020/ The 21st International Society for Music Information Retrieval Conference], ISMIR 2020, which will be held in Montréal, Canada, October 11–15, 2020.

J. Stephen Downie 
Director, IMIRSEL 

==Task Leadership Model==

Like previous years, we are prepared to improve the distribution of tasks for the upcoming MIREX 2020. To do so, we really need leaders to help us organize and run each task.

To volunteer to lead a task, please complete the form [https://forms.gle/9idWhxPgdisxFW55A here]. Current information about task captains can be found on the [[2020:Task Captains]] page. Please direct any communication to the [https://lists.ischool.illinois.edu/lists/admin/evalfest EvalFest] mailing list.

What does it mean to lead a task?
* Update wiki pages as needed
* Communicate with submitters and troubleshooting submissions
* Execution and evaluation of submissions
* Publishing final results

Due to the proprietary nature of much of the data, the submission system, evaluation framework, and most of the datasets will continue to be hosted by IMIRSEL. However, we are prepared to provide access to task organizers to manage and run submissions on the IMIRSEL systems.

We really need leaders to help us!

==MIREX 2020 Deadline Dates==
* '''August 30th 2020'''
** [[2020:Audio Fingerprinting]] <TC: Chung-Che Wang>
** [[2020:Audio Classification (Train/Test) Tasks]] <TC: Yun Hao (IMIRSEL)>, including
*** Audio US Pop Genre Classification
*** Audio Latin Genre Classification
*** Audio Music Mood Classification
*** Audio Classical Composer Identification
** [[2020:Audio K-POP Mood Classification]] <TC: Yun Hao (IMIRSEL)>
** [[2020:Audio K-POP Genre Classification]] <TC: Yun Hao (IMIRSEL)>
** [[2020:Audio Tag Classification]] <TC: Emre Demir>

* '''September 6th 2020'''
** [[2020:Audio Chord Estimation]] <TC: Johan Pauwels>
** [[2020:Audio Cover Song Identification]] <TC: Yun Hao (IMIRSEL)>
** [[2020:Audio Downbeat Estimation]] <TC: Mickaël Zehren>
** [[2020:Audio Key Detection]] <TC: Johan Pauwels>
** [[2020:Audio Melody Extraction]] <TC: An-Qi Huang>
** [[2020:Patterns for Prediction]] (offshoot of [[2017:Discovery of Repeated Themes & Sections]]) <TC: Berit Janssen, Iris Ren, and Tom Collins>
** [[2020:Query by Singing/Humming]] <TC: Makarand Velankar>
** [[2020:Multiple Fundamental Frequency Estimation & Tracking]] <TC: Yun Hao (IMIRSEL)>
** [[2020:Lyrics Transcription]] (former: Automatic Lyrics-to-Audio Alignment) <TC: Georgi Dzhambazov, Daniel Stoller>

* '''September 13th 2020'''
** '''''NEW!''''' [[2020:Singing_Transcription_from_Polyphonic_Music]] <TC: Jun-You Wang>

==MIREX 2020 Submission Instructions==
* Be sure to read through the rest of this page
* Be sure to read though the task pages for which you are submitting
* Be sure to follow the [[2009:Best Coding Practices for MIREX | Best Coding Practices for MIREX]]
* Be sure to follow the [[MIREX 2020 Submission Instructions]] including both the tutorial video and the text
* The MIREX 2020 Submission System is coming soon at: https://www.music-ir.org/mirex/sub/.

==MIREX 2020 Evaluation==

===Note to New Participants===
Please take the time to read the following review articles that explain the history and structure of MIREX.

Downie, J. Stephen (2008). The Music Information Retrieval Evaluation Exchange (2005-2007): 
A window into music information retrieval research.''Acoustical Science and Technology 29'' (4): 247-255. 
Available at: [http://dx.doi.org/10.1250/ast.29.247 http://dx.doi.org/10.1250/ast.29.247]

Downie, J. Stephen, Andreas F. Ehmann, Mert Bay and M. Cameron Jones. (2010). 
The Music Information Retrieval Evaluation eXchange: Some Observations and Insights. 
''Advances in Music Information Retrieval'' Vol. 274, pp. 93-115 
Available at: [http://bit.ly/KpM5u5 http://bit.ly/KpM5u5]

===Runtime Limits===

We reserve the right to stop any process that exceeds runtime limits for each task. We will do our best to notify you in enough time to allow revisions, but this may not be possible in some cases. Please respect the published runtime limits.

===Note to All Participants===

Because MIREX is premised upon the sharing of ideas and results, '''ALL''' MIREX participants are expected to:

# submit a DRAFT 2-3 page extended abstract PDF in the ISMIR format about the submitted program(s) to help us and the community better understand how the algorithm works when submitting their programme(s).
# submit a FINALIZED 2-3 page extended abstract PDF in the ISMIR format prior to ISMIR 2020 for posting on the respective results pages (sometimes the same abstract can be used for multiple submissions; in many cases the DRAFT and FINALIZED abstracts are the same).
# present a poster at the MIREX 2020 poster session at ISMIR 2020, if there is a physical component to the conference.

===Software Dependency Requests===
If you have not submitted to MIREX before or are unsure whether IMIRSEL currently supports some of the software/architecture dependencies for your submission, please contact [mailto:yunhao2@illinois.edu IMIRSEL team] as early as possible. Failing to notify the team might result in your submission being rejected.

Finally, you will also be expected to detail your software/architecture dependencies in a README file to be provided to the submission system.

==Getting Involved in MIREX 2020==
MIREX is a community-based endeavour. Be a part of the community and help make MIREX 2020 the best yet.

===Mailing List Participation===
If you are interested in formal MIR evaluation, you should also subscribe to the "MIREX" (aka "EvalFest") mail list and participate in the community discussions about defining and running MIREX 2020 tasks. To subscribe to EvalFest, send a message to [mailto:lists@ischool.illinois.edu lists@ischool.illinois.edu] with the subject line “subscribe evalfest”

If you are participating in MIREX 2020, it is VERY IMPORTANT that you are subscribed to EvalFest. Deadlines, task updates and other important information will be announced via this mailing list. Please use the EvalFest for discussion of MIREX task proposals and other MIREX related issues. This wiki (MIREX 2020 wiki) will be used to embody and disseminate task proposals, however, task related discussions should be conducted on the MIREX organization mailing list (EvalFest) rather than on this wiki, but should be summarized here.

Where possible, definitions or example code for new evaluation metrics or tasks should be provided to the IMIRSEL team who will embody them in software as part of the NEMA analytics framework, which will be released to the community at or before ISMIR 2020 - providing a standardised set of interfaces and output to disciplined evaluation procedures for a great many MIR tasks.

===Wiki Participation===
If you find that you cannot edit a MIREX wiki page, you will need to create a new account via: [[Special:Userlogin]].

Please note that because of "spam-bots", MIREX wiki registration requests may be moderated by IMIRSEL members. It might take up to 24 hours for approval (Thank you for your patience!).

==MIREX 2005 - 2019 Wikis==
Content from MIREX 2005 - 2018 are available at:
'''[[2019:Main_Page|MIREX 2019]]'''
'''[[2018:Main_Page|MIREX 2018]]'''
'''[[2017:Main_Page|MIREX 2017]]'''
'''[[2016:Main_Page|MIREX 2016]]'''
'''[[2015:Main_Page|MIREX 2015]]'''
'''[[2014:Main_Page|MIREX 2014]]'''
'''[[2013:Main_Page|MIREX 2013]]'''
'''[[2012:Main_Page|MIREX 2012]]'''
'''[[2011:Main_Page|MIREX 2011]]'''
'''[[2010:Main_Page|MIREX 2010]]'''
'''[[2009:Main_Page|MIREX 2009]]'''
'''[[2008:Main_Page|MIREX 2008]]'''
'''[[2007:Main_Page|MIREX 2007]]'''
'''[[2006:Main_Page|MIREX 2006]]'''
'''[[2005:Main_Page|MIREX 2005]]'''

2020:Main Page

2020-08-31T23:46:40Z

Yun Hao: /* Mailing List Participation */

==Welcome to MIREX 2020==

This is the main page for the 16th running of the Music Information Retrieval Evaluation eXchange (MIREX 2020). The International Music Information Retrieval Systems Evaluation Laboratory (IMIRSEL) at [https://ischool.illinois.edu School of Information Sciences], University of Illinois at Urbana-Champaign ([https://illinois.edu UIUC]) is the principal organizer of MIREX 2020.

The MIREX 2020 community will hold its annual meeting as part of [https://ismir.github.io/ISMIR2020/ The 21st International Society for Music Information Retrieval Conference], ISMIR 2020, which will be held in Montréal, Canada, October 11–15, 2020.

J. Stephen Downie 
Director, IMIRSEL 

==Task Leadership Model==

Like previous years, we are prepared to improve the distribution of tasks for the upcoming MIREX 2020. To do so, we really need leaders to help us organize and run each task.

To volunteer to lead a task, please complete the form [https://forms.gle/9idWhxPgdisxFW55A here]. Current information about task captains can be found on the [[2020:Task Captains]] page. Please direct any communication to the [https://lists.ischool.illinois.edu/lists/admin/evalfest EvalFest] mailing list.

What does it mean to lead a task?
* Update wiki pages as needed
* Communicate with submitters and troubleshooting submissions
* Execution and evaluation of submissions
* Publishing final results

Due to the proprietary nature of much of the data, the submission system, evaluation framework, and most of the datasets will continue to be hosted by IMIRSEL. However, we are prepared to provide access to task organizers to manage and run submissions on the IMIRSEL systems.

We really need leaders to help us!
==MIREX 2020 Deadline Dates==
* '''August 30th 2020'''
** [[2020:Audio Fingerprinting]] <TC: Chung-Che Wang>
** [[2020:Audio Classification (Train/Test) Tasks]] <TC: Yun Hao (IMIRSEL)>, including
*** Audio US Pop Genre Classification
*** Audio Latin Genre Classification
*** Audio Music Mood Classification
*** Audio Classical Composer Identification
** [[2020:Audio K-POP Mood Classification]] <TC: Yun Hao (IMIRSEL)>
** [[2020:Audio K-POP Genre Classification]] <TC: Yun Hao (IMIRSEL)>
** [[2020:Audio Tag Classification]] <TC: Emre Demir>

* '''September 6th 2020'''
** [[2020:Audio Chord Estimation]] <TC: Johan Pauwels>
** [[2020:Audio Cover Song Identification]] <TC: Yun Hao (IMIRSEL)>
** [[2020:Audio Downbeat Estimation]] <TC: Mickaël Zehren>
** [[2020:Audio Key Detection]] <TC: Johan Pauwels>
** [[2020:Audio Melody Extraction]] <TC: An-Qi Huang>
** [[2020:Patterns for Prediction]] (offshoot of [[2017:Discovery of Repeated Themes & Sections]]) <TC: Berit Janssen, Iris Ren, and Tom Collins>
** [[2020:Query by Singing/Humming]] <TC: Makarand Velankar>
** [[2020:Multiple Fundamental Frequency Estimation & Tracking]] <TC: Yun Hao (IMIRSEL)>

* '''September 13th 2020'''
** '''''NEW!''''' [[2020:Singing_Transcription_from_Polyphonic_Music]] <TC: Jun-You Wang>
** [[2020:Lyrics Transcription]] (former: Automatic Lyrics-to-Audio Alignment) <TC: Georgi Dzhambazov, Chitralekha Gupta, Daniel Stoller>

==MIREX 2020 Submission Instructions==
* Be sure to read through the rest of this page
* Be sure to read though the task pages for which you are submitting
* Be sure to follow the [[2009:Best Coding Practices for MIREX | Best Coding Practices for MIREX]]
* Be sure to follow the [[MIREX 2019 Submission Instructions]] including both the tutorial video and the text
* The MIREX 2020 Submission System is coming soon at: https://www.music-ir.org/mirex/sub/.

==MIREX 2020 Evaluation==

===Note to New Participants===
Please take the time to read the following review articles that explain the history and structure of MIREX.

Downie, J. Stephen (2008). The Music Information Retrieval Evaluation Exchange (2005-2007): 
A window into music information retrieval research.''Acoustical Science and Technology 29'' (4): 247-255. 
Available at: [http://dx.doi.org/10.1250/ast.29.247 http://dx.doi.org/10.1250/ast.29.247]

Downie, J. Stephen, Andreas F. Ehmann, Mert Bay and M. Cameron Jones. (2010). 
The Music Information Retrieval Evaluation eXchange: Some Observations and Insights. 
''Advances in Music Information Retrieval'' Vol. 274, pp. 93-115 
Available at: [http://bit.ly/KpM5u5 http://bit.ly/KpM5u5]

===Runtime Limits===

We reserve the right to stop any process that exceeds runtime limits for each task. We will do our best to notify you in enough time to allow revisions, but this may not be possible in some cases. Please respect the published runtime limits.

===Note to All Participants===

Because MIREX is premised upon the sharing of ideas and results, '''ALL''' MIREX participants are expected to:

# submit a DRAFT 2-3 page extended abstract PDF in the ISMIR format about the submitted program(s) to help us and the community better understand how the algorithm works when submitting their programme(s).
# submit a FINALIZED 2-3 page extended abstract PDF in the ISMIR format prior to ISMIR 2020 for posting on the respective results pages (sometimes the same abstract can be used for multiple submissions; in many cases the DRAFT and FINALIZED abstracts are the same).
# present a poster at the MIREX 2020 poster session at ISMIR 2020, if there is a physical component to the conference.

===Software Dependency Requests===
If you have not submitted to MIREX before or are unsure whether IMIRSEL currently supports some of the software/architecture dependencies for your submission, please contact [mailto:yunhao2@illinois.edu IMIRSEL team] as early as possible. Failing to notify the team might result in your submission being rejected.

Finally, you will also be expected to detail your software/architecture dependencies in a README file to be provided to the submission system.

==Getting Involved in MIREX 2020==
MIREX is a community-based endeavour. Be a part of the community and help make MIREX 2020 the best yet.

===Mailing List Participation===
If you are interested in formal MIR evaluation, you should also subscribe to the "MIREX" (aka "EvalFest") mail list and participate in the community discussions about defining and running MIREX 2020 tasks. To subscribe to EvalFest, send a message to [mailto:lists@ischool.illinois.edu lists@ischool.illinois.edu] with the subject line “subscribe evalfest”

If you are participating in MIREX 2020, it is VERY IMPORTANT that you are subscribed to EvalFest. Deadlines, task updates and other important information will be announced via this mailing list. Please use the EvalFest for discussion of MIREX task proposals and other MIREX related issues. This wiki (MIREX 2020 wiki) will be used to embody and disseminate task proposals, however, task related discussions should be conducted on the MIREX organization mailing list (EvalFest) rather than on this wiki, but should be summarized here.

Where possible, definitions or example code for new evaluation metrics or tasks should be provided to the IMIRSEL team who will embody them in software as part of the NEMA analytics framework, which will be released to the community at or before ISMIR 2020 - providing a standardised set of interfaces and output to disciplined evaluation procedures for a great many MIR tasks.

===Wiki Participation===
If you find that you cannot edit a MIREX wiki page, you will need to create a new account via: [[Special:Userlogin]].

Please note that because of "spam-bots", MIREX wiki registration requests may be moderated by IMIRSEL members. It might take up to 24 hours for approval (Thank you for your patience!).

==MIREX 2005 - 2019 Wikis==
Content from MIREX 2005 - 2018 are available at:
'''[[2019:Main_Page|MIREX 2019]]'''
'''[[2018:Main_Page|MIREX 2018]]'''
'''[[2017:Main_Page|MIREX 2017]]'''
'''[[2016:Main_Page|MIREX 2016]]'''
'''[[2015:Main_Page|MIREX 2015]]'''
'''[[2014:Main_Page|MIREX 2014]]'''
'''[[2013:Main_Page|MIREX 2013]]'''
'''[[2012:Main_Page|MIREX 2012]]'''
'''[[2011:Main_Page|MIREX 2011]]'''
'''[[2010:Main_Page|MIREX 2010]]'''
'''[[2009:Main_Page|MIREX 2009]]'''
'''[[2008:Main_Page|MIREX 2008]]'''
'''[[2007:Main_Page|MIREX 2007]]'''
'''[[2006:Main_Page|MIREX 2006]]'''
'''[[2005:Main_Page|MIREX 2005]]'''

2020:Main Page

2020-08-31T23:45:46Z

Yun Hao: /* Mailing List Participation */

==Welcome to MIREX 2020==

This is the main page for the 16th running of the Music Information Retrieval Evaluation eXchange (MIREX 2020). The International Music Information Retrieval Systems Evaluation Laboratory (IMIRSEL) at [https://ischool.illinois.edu School of Information Sciences], University of Illinois at Urbana-Champaign ([https://illinois.edu UIUC]) is the principal organizer of MIREX 2020.

The MIREX 2020 community will hold its annual meeting as part of [https://ismir.github.io/ISMIR2020/ The 21st International Society for Music Information Retrieval Conference], ISMIR 2020, which will be held in Montréal, Canada, October 11–15, 2020.

J. Stephen Downie 
Director, IMIRSEL 

==Task Leadership Model==

Like previous years, we are prepared to improve the distribution of tasks for the upcoming MIREX 2020. To do so, we really need leaders to help us organize and run each task.

To volunteer to lead a task, please complete the form [https://forms.gle/9idWhxPgdisxFW55A here]. Current information about task captains can be found on the [[2020:Task Captains]] page. Please direct any communication to the [https://lists.ischool.illinois.edu/lists/admin/evalfest EvalFest] mailing list.

What does it mean to lead a task?
* Update wiki pages as needed
* Communicate with submitters and troubleshooting submissions
* Execution and evaluation of submissions
* Publishing final results

Due to the proprietary nature of much of the data, the submission system, evaluation framework, and most of the datasets will continue to be hosted by IMIRSEL. However, we are prepared to provide access to task organizers to manage and run submissions on the IMIRSEL systems.

We really need leaders to help us!
==MIREX 2020 Deadline Dates==
* '''August 30th 2020'''
** [[2020:Audio Fingerprinting]] <TC: Chung-Che Wang>
** [[2020:Audio Classification (Train/Test) Tasks]] <TC: Yun Hao (IMIRSEL)>, including
*** Audio US Pop Genre Classification
*** Audio Latin Genre Classification
*** Audio Music Mood Classification
*** Audio Classical Composer Identification
** [[2020:Audio K-POP Mood Classification]] <TC: Yun Hao (IMIRSEL)>
** [[2020:Audio K-POP Genre Classification]] <TC: Yun Hao (IMIRSEL)>
** [[2020:Audio Tag Classification]] <TC: Emre Demir>

* '''September 6th 2020'''
** [[2020:Audio Chord Estimation]] <TC: Johan Pauwels>
** [[2020:Audio Cover Song Identification]] <TC: Yun Hao (IMIRSEL)>
** [[2020:Audio Downbeat Estimation]] <TC: Mickaël Zehren>
** [[2020:Audio Key Detection]] <TC: Johan Pauwels>
** [[2020:Audio Melody Extraction]] <TC: An-Qi Huang>
** [[2020:Patterns for Prediction]] (offshoot of [[2017:Discovery of Repeated Themes & Sections]]) <TC: Berit Janssen, Iris Ren, and Tom Collins>
** [[2020:Query by Singing/Humming]] <TC: Makarand Velankar>
** [[2020:Multiple Fundamental Frequency Estimation & Tracking]] <TC: Yun Hao (IMIRSEL)>

* '''September 13th 2020'''
** '''''NEW!''''' [[2020:Singing_Transcription_from_Polyphonic_Music]] <TC: Jun-You Wang>
** [[2020:Lyrics Transcription]] (former: Automatic Lyrics-to-Audio Alignment) <TC: Georgi Dzhambazov, Chitralekha Gupta, Daniel Stoller>

==MIREX 2020 Submission Instructions==
* Be sure to read through the rest of this page
* Be sure to read though the task pages for which you are submitting
* Be sure to follow the [[2009:Best Coding Practices for MIREX | Best Coding Practices for MIREX]]
* Be sure to follow the [[MIREX 2019 Submission Instructions]] including both the tutorial video and the text
* The MIREX 2020 Submission System is coming soon at: https://www.music-ir.org/mirex/sub/.

==MIREX 2020 Evaluation==

===Note to New Participants===
Please take the time to read the following review articles that explain the history and structure of MIREX.

Downie, J. Stephen (2008). The Music Information Retrieval Evaluation Exchange (2005-2007): 
A window into music information retrieval research.''Acoustical Science and Technology 29'' (4): 247-255. 
Available at: [http://dx.doi.org/10.1250/ast.29.247 http://dx.doi.org/10.1250/ast.29.247]

Downie, J. Stephen, Andreas F. Ehmann, Mert Bay and M. Cameron Jones. (2010). 
The Music Information Retrieval Evaluation eXchange: Some Observations and Insights. 
''Advances in Music Information Retrieval'' Vol. 274, pp. 93-115 
Available at: [http://bit.ly/KpM5u5 http://bit.ly/KpM5u5]

===Runtime Limits===

We reserve the right to stop any process that exceeds runtime limits for each task. We will do our best to notify you in enough time to allow revisions, but this may not be possible in some cases. Please respect the published runtime limits.

===Note to All Participants===

Because MIREX is premised upon the sharing of ideas and results, '''ALL''' MIREX participants are expected to:

# submit a DRAFT 2-3 page extended abstract PDF in the ISMIR format about the submitted program(s) to help us and the community better understand how the algorithm works when submitting their programme(s).
# submit a FINALIZED 2-3 page extended abstract PDF in the ISMIR format prior to ISMIR 2020 for posting on the respective results pages (sometimes the same abstract can be used for multiple submissions; in many cases the DRAFT and FINALIZED abstracts are the same).
# present a poster at the MIREX 2020 poster session at ISMIR 2020, if there is a physical component to the conference.

===Software Dependency Requests===
If you have not submitted to MIREX before or are unsure whether IMIRSEL currently supports some of the software/architecture dependencies for your submission, please contact [mailto:yunhao2@illinois.edu IMIRSEL team] as early as possible. Failing to notify the team might result in your submission being rejected.

Finally, you will also be expected to detail your software/architecture dependencies in a README file to be provided to the submission system.

==Getting Involved in MIREX 2020==
MIREX is a community-based endeavour. Be a part of the community and help make MIREX 2020 the best yet.

===Mailing List Participation===
If you are interested in formal MIR evaluation, you should also subscribe to the "MIREX" (aka "EvalFest") mail list and participate in the community discussions about defining and running MIREX 2020 tasks. To subscribe to EvalFest, send a message to <lists@ischool.illinois.edu> with the subject line “subscribe evalfest”

If you are participating in MIREX 2020, it is VERY IMPORTANT that you are subscribed to EvalFest. Deadlines, task updates and other important information will be announced via this mailing list. Please use the EvalFest for discussion of MIREX task proposals and other MIREX related issues. This wiki (MIREX 2020 wiki) will be used to embody and disseminate task proposals, however, task related discussions should be conducted on the MIREX organization mailing list (EvalFest) rather than on this wiki, but should be summarized here.

Where possible, definitions or example code for new evaluation metrics or tasks should be provided to the IMIRSEL team who will embody them in software as part of the NEMA analytics framework, which will be released to the community at or before ISMIR 2020 - providing a standardised set of interfaces and output to disciplined evaluation procedures for a great many MIR tasks.

===Wiki Participation===
If you find that you cannot edit a MIREX wiki page, you will need to create a new account via: [[Special:Userlogin]].

Please note that because of "spam-bots", MIREX wiki registration requests may be moderated by IMIRSEL members. It might take up to 24 hours for approval (Thank you for your patience!).

==MIREX 2005 - 2019 Wikis==
Content from MIREX 2005 - 2018 are available at:
'''[[2019:Main_Page|MIREX 2019]]'''
'''[[2018:Main_Page|MIREX 2018]]'''
'''[[2017:Main_Page|MIREX 2017]]'''
'''[[2016:Main_Page|MIREX 2016]]'''
'''[[2015:Main_Page|MIREX 2015]]'''
'''[[2014:Main_Page|MIREX 2014]]'''
'''[[2013:Main_Page|MIREX 2013]]'''
'''[[2012:Main_Page|MIREX 2012]]'''
'''[[2011:Main_Page|MIREX 2011]]'''
'''[[2010:Main_Page|MIREX 2010]]'''
'''[[2009:Main_Page|MIREX 2009]]'''
'''[[2008:Main_Page|MIREX 2008]]'''
'''[[2007:Main_Page|MIREX 2007]]'''
'''[[2006:Main_Page|MIREX 2006]]'''
'''[[2005:Main_Page|MIREX 2005]]'''

2020:Task Captains

2020-08-31T23:37:18Z

Yun Hao:

Like MIREX 2019, we are prepared to improve the distribution of tasks for the upcoming MIREX 2020. To do so, we really need leaders to help us organize and run each task.

To volunteer to lead one or more tasks, please complete the form [https://goo.gl/forms/0w5nowHkHzYxHl4l1 here]. Please direct any communication to the [https://lists.ischool.illinois.edu/lists/admin/evalfest EvalFest] mailing list.

What does it mean to lead a task?
* Update wiki pages as needed
* Communicate with submitters and troubleshooting submissions
* Execution and evaluation of submissions
* Publishing final results

Due to the proprietary nature of much of the data, the submission system, evaluation framework, and most of the datasets will continue to be hosted by IMIRSEL. However, we are prepared to provide access to task organizers to manage and run submissions on the IMIRSEL systems.

{| class="wikitable" style="margin-left: 20px"
!ID !! Task !! Captain(s)
|-
|act
|[[2020:Audio Classification (Train/Test) Tasks]]
|[mailto:yunhao2@illinois.edu Yun Hao (IMIRSEL)]
|-
|ace
|[[2020:Audio Chord Estimation]]
|[mailto:j.pauwels@qmul.ac.uk Johan Pauwels]
|-
|acs
|[[2020:Audio Cover Song Identification]]
|[mailto:yunhao2@illinois.edu Yun Hao (IMIRSEL)]
|-
|ade
|[[2020:Audio Downbeat Estimation]]
|[mailto:zehren@aices.rwth-aachen.de Mickaël Zehren]
|-
|afp
|[[2020:Audio Fingerprinting]]
|[mailto:geniusturtle@mirlab.org Chung-Che Wang]
|-
|akd
|[[2020:Audio Key Detection]]
|[mailto:j.pauwels@qmul.ac.uk Johan Pauwels]
|-
|lt
|[[2020:Lyrics Transcription]]
|[mailto:info@voicemagix.com Georgi Dzhambazov]|[mailto:d.stoller@qmul.ac.uk Daniel Stoller]
|-
|mf0
|[[2020:Multiple Fundamental Frequency Estimation & Tracking]]
|[mailto:yunhao2@illinois.edu Yun Hao (IMIRSEL)]
|-
|pfp
|[[2020:Patterns for Prediction]]
|[mailto:yuping.ren.iris@gmail.com Iris Ren][mailto:berit.janssen@gmail.com Berit Janssen][mailto:toc215@lehigh.edu Tom Collins]
|-
|ame
|[[2020:Audio Melody Extraction]]
|[mailto:16171395@qq.com An-Qi Huang]
|-
|qbsh
|[[2020:Query by Singing/Humming]]
|[mailto:makarand.velankar@cumminscollege.in Makarand Velankar]
|-
|atg
|[[2020:Audio Tag Classification ]]
|[mailto:demir1260@gmail.com Emre Demir]
|-
|stpm
|[[2020:Singing Transcription from Polyphonic Music]]
|[mailto:b06902046@ntu.edu.tw Jun-You Wang]
|}

2020:Task Captains

2020-08-31T23:36:49Z

Yun Hao:

Like MIREX 2019, we are prepared to improve the distribution of tasks for the upcoming MIREX 2020. To do so, we really need leaders to help us organize and run each task.

To volunteer to lead one or more tasks, please complete the form [https://goo.gl/forms/0w5nowHkHzYxHl4l1 here]. Please direct any communication to the [https://lists.ischool.illinois.edu/lists/admin/evalfest EvalFest] mailing list.

What does it mean to lead a task?
* Update wiki pages as needed
* Communicate with submitters and troubleshooting submissions
* Execution and evaluation of submissions
* Publishing final results

Due to the proprietary nature of much of the data, the submission system, evaluation framework, and most of the datasets will continue to be hosted by IMIRSEL. However, we are prepared to provide access to task organizers to manage and run submissions on the IMIRSEL systems.

{| class="wikitable" style="margin-left: 20px"
!ID !! Task !! Captain(s)
|-
|act
|[[2020:Audio Classification (Train/Test) Tasks]]
|[mailto:yunhao2@illinois.edu Yun Hao (IMIRSEL)]
|-
|ace
|[[2020:Audio Chord Estimation]]
|[mailto:j.pauwels@qmul.ac.uk Johan Pauwels]
|-
|acs
|[[2020:Audio Cover Song Identification]]
|[mailto:yunhao2@illinois.edu Yun Hao (IMIRSEL)]
|-
|ade
|[[2020:Audio Downbeat Estimation]]
|[mailto:zehren@aices.rwth-aachen.de Mickaël Zehren]
|-
|afp
|[[2020:Audio Fingerprinting]]
|[mailto:geniusturtle@mirlab.org Chung-Che Wang]
|-
|akd
|[[2020:Audio Key Detection]]
|[mailto:j.pauwels@qmul.ac.uk Johan Pauwels]
|-
|lt
|[[2020:Lyrics Transcription]]
|[mailto:info@voicemagix.com Georgi Dzhambazov]|[mailto:d.stoller@qmul.ac.uk Daniel Stoller]
|-
|mf0
|[[2020:Multiple Fundamental Frequency Estimation & Tracking]]
|[mailto:yunhao2@illinois.edu Yun Hao (IMIRSEL)]
|-
|pfp
|[[2020:Patterns for Prediction]]
|[mailto:yuping.ren.iris@gmail.com Iris Ren]|[mailto:berit.janssen@gmail.com Berit Janssen]|[mailto:toc215@lehigh.edu Tom Collins]
|-
|ame
|[[2020:Audio Melody Extraction]]
|[mailto:16171395@qq.com An-Qi Huang]
|-
|qbsh
|[[2020:Query by Singing/Humming]]
|[mailto:makarand.velankar@cumminscollege.in Makarand Velankar]
|-
|atg
|[[2020:Audio Tag Classification ]]
|[mailto:demir1260@gmail.com Emre Demir]
|-
|stpm
|[[2020:Singing Transcription from Polyphonic Music]]
|[mailto:b06902046@ntu.edu.tw Jun-You Wang]
|}

2020:Main Page

2020-08-25T17:21:20Z

Yun Hao: /* MIREX 2020 Deadline Dates */

==Welcome to MIREX 2020==

This is the main page for the 16th running of the Music Information Retrieval Evaluation eXchange (MIREX 2020). The International Music Information Retrieval Systems Evaluation Laboratory (IMIRSEL) at [https://ischool.illinois.edu School of Information Sciences], University of Illinois at Urbana-Champaign ([https://illinois.edu UIUC]) is the principal organizer of MIREX 2020.

The MIREX 2020 community will hold its annual meeting as part of [https://ismir.github.io/ISMIR2020/ The 21st International Society for Music Information Retrieval Conference], ISMIR 2020, which will be held in Montréal, Canada, October 11–15, 2020.

J. Stephen Downie 
Director, IMIRSEL 

==Task Leadership Model==

Like previous years, we are prepared to improve the distribution of tasks for the upcoming MIREX 2020. To do so, we really need leaders to help us organize and run each task.

To volunteer to lead a task, please complete the form [https://forms.gle/9idWhxPgdisxFW55A here]. Current information about task captains can be found on the [[2020:Task Captains]] page. Please direct any communication to the [https://lists.ischool.illinois.edu/lists/admin/evalfest EvalFest] mailing list.

What does it mean to lead a task?
* Update wiki pages as needed
* Communicate with submitters and troubleshooting submissions
* Execution and evaluation of submissions
* Publishing final results

Due to the proprietary nature of much of the data, the submission system, evaluation framework, and most of the datasets will continue to be hosted by IMIRSEL. However, we are prepared to provide access to task organizers to manage and run submissions on the IMIRSEL systems.

We really need leaders to help us!
==MIREX 2020 Deadline Dates==
* '''August 30th 2020'''
** [[2020:Audio Fingerprinting]] <TC: Chung-Che Wang>
** [[2020:Audio Classification (Train/Test) Tasks]] <TC: Yun Hao (IMIRSEL)>, including
*** Audio US Pop Genre Classification
*** Audio Latin Genre Classification
*** Audio Music Mood Classification
*** Audio Classical Composer Identification
** [[2020:Audio K-POP Mood Classification]] <TC: Yun Hao (IMIRSEL)>
** [[2020:Audio K-POP Genre Classification]] <TC: Yun Hao (IMIRSEL)>
** [[2020:Audio Tag Classification]] <TC: Emre Demir>

* '''September 6th 2020'''
** [[2020:Audio Chord Estimation]] <TC: Johan Pauwels>
** [[2020:Audio Cover Song Identification]] <TC: Yun Hao (IMIRSEL)>
** [[2020:Audio Downbeat Estimation]] <TC: Mickaël Zehren>
** [[2020:Audio Key Detection]] <TC: Johan Pauwels>
** [[2020:Audio Melody Extraction]] <TC: An-Qi Huang>
** [[2020:Patterns for Prediction]] (offshoot of [[2017:Discovery of Repeated Themes & Sections]]) <TC: Berit Janssen, Iris Ren, and Tom Collins>
** [[2020:Query by Singing/Humming]] <TC: Makarand Velankar>
** [[2020:Multiple Fundamental Frequency Estimation & Tracking]] <TC: Yun Hao (IMIRSEL)>
** [[2020:Lyrics Transcription]] (former: Automatic Lyrics-to-Audio Alignment) <TC: Georgi Dzhambazov, Daniel Stoller>

* '''September 13th 2020'''
** '''''NEW!''''' [[2020:Singing_Transcription_from_Polyphonic_Music]] <TC: Jun-You Wang>

==MIREX 2020 Submission Instructions==
* Be sure to read through the rest of this page
* Be sure to read though the task pages for which you are submitting
* Be sure to follow the [[2009:Best Coding Practices for MIREX | Best Coding Practices for MIREX]]
* Be sure to follow the [[MIREX 2019 Submission Instructions]] including both the tutorial video and the text
* The MIREX 2020 Submission System is coming soon at: https://www.music-ir.org/mirex/sub/.

==MIREX 2020 Evaluation==

===Note to New Participants===
Please take the time to read the following review articles that explain the history and structure of MIREX.

Downie, J. Stephen (2008). The Music Information Retrieval Evaluation Exchange (2005-2007): 
A window into music information retrieval research.''Acoustical Science and Technology 29'' (4): 247-255. 
Available at: [http://dx.doi.org/10.1250/ast.29.247 http://dx.doi.org/10.1250/ast.29.247]

Downie, J. Stephen, Andreas F. Ehmann, Mert Bay and M. Cameron Jones. (2010). 
The Music Information Retrieval Evaluation eXchange: Some Observations and Insights. 
''Advances in Music Information Retrieval'' Vol. 274, pp. 93-115 
Available at: [http://bit.ly/KpM5u5 http://bit.ly/KpM5u5]

===Runtime Limits===

We reserve the right to stop any process that exceeds runtime limits for each task. We will do our best to notify you in enough time to allow revisions, but this may not be possible in some cases. Please respect the published runtime limits.

===Note to All Participants===

Because MIREX is premised upon the sharing of ideas and results, '''ALL''' MIREX participants are expected to:

# submit a DRAFT 2-3 page extended abstract PDF in the ISMIR format about the submitted program(s) to help us and the community better understand how the algorithm works when submitting their programme(s).
# submit a FINALIZED 2-3 page extended abstract PDF in the ISMIR format prior to ISMIR 2020 for posting on the respective results pages (sometimes the same abstract can be used for multiple submissions; in many cases the DRAFT and FINALIZED abstracts are the same).
# present a poster at the MIREX 2020 poster session at ISMIR 2020, if there is a physical component to the conference.

===Software Dependency Requests===
If you have not submitted to MIREX before or are unsure whether IMIRSEL currently supports some of the software/architecture dependencies for your submission, please contact [mailto:yunhao2@illinois.edu IMIRSEL team] as early as possible. Failing to notify the team might result in your submission being rejected.

Finally, you will also be expected to detail your software/architecture dependencies in a README file to be provided to the submission system.

==Getting Involved in MIREX 2020==
MIREX is a community-based endeavour. Be a part of the community and help make MIREX 2020 the best yet.

===Mailing List Participation===
If you are interested in formal MIR evaluation, you should also subscribe to the "MIREX" (aka "EvalFest") mail list and participate in the community discussions about defining and running MIREX 2020 tasks. Subscription information at:
[https://mail.lis.illinois.edu/mailman/listinfo/evalfest EvalFest Central].

If you are participating in MIREX 2020, it is VERY IMPORTANT that you are subscribed to EvalFest. Deadlines, task updates and other important information will be announced via this mailing list. Please use the EvalFest for discussion of MIREX task proposals and other MIREX related issues. This wiki (MIREX 2020 wiki) will be used to embody and disseminate task proposals, however, task related discussions should be conducted on the MIREX organization mailing list (EvalFest) rather than on this wiki, but should be summarized here.

Where possible, definitions or example code for new evaluation metrics or tasks should be provided to the IMIRSEL team who will embody them in software as part of the NEMA analytics framework, which will be released to the community at or before ISMIR 2020 - providing a standardised set of interfaces and output to disciplined evaluation procedures for a great many MIR tasks.

===Wiki Participation===
If you find that you cannot edit a MIREX wiki page, you will need to create a new account via: [[Special:Userlogin]].

Please note that because of "spam-bots", MIREX wiki registration requests may be moderated by IMIRSEL members. It might take up to 24 hours for approval (Thank you for your patience!).

==MIREX 2005 - 2019 Wikis==
Content from MIREX 2005 - 2018 are available at:
'''[[2019:Main_Page|MIREX 2019]]'''
'''[[2018:Main_Page|MIREX 2018]]'''
'''[[2017:Main_Page|MIREX 2017]]'''
'''[[2016:Main_Page|MIREX 2016]]'''
'''[[2015:Main_Page|MIREX 2015]]'''
'''[[2014:Main_Page|MIREX 2014]]'''
'''[[2013:Main_Page|MIREX 2013]]'''
'''[[2012:Main_Page|MIREX 2012]]'''
'''[[2011:Main_Page|MIREX 2011]]'''
'''[[2010:Main_Page|MIREX 2010]]'''
'''[[2009:Main_Page|MIREX 2009]]'''
'''[[2008:Main_Page|MIREX 2008]]'''
'''[[2007:Main_Page|MIREX 2007]]'''
'''[[2006:Main_Page|MIREX 2006]]'''
'''[[2005:Main_Page|MIREX 2005]]'''

MIREX HOME

2020-08-25T17:21:04Z

Yun Hao: /* MIREX 2020 Deadline Dates */

==Welcome to MIREX 2020==

This is the main page for the 16th running of the Music Information Retrieval Evaluation eXchange (MIREX 2020). The International Music Information Retrieval Systems Evaluation Laboratory (IMIRSEL) at [https://ischool.illinois.edu School of Information Sciences], University of Illinois at Urbana-Champaign ([https://illinois.edu UIUC]) is the principal organizer of MIREX 2020.

The MIREX 2020 community will hold its annual meeting as part of [https://ismir.github.io/ISMIR2020/ The 21st International Society for Music Information Retrieval Conference], ISMIR 2020, which will be held in Montréal, Canada, October 11–15, 2020.

J. Stephen Downie 
Director, IMIRSEL 

==Task Leadership Model==

Like previous years, we are prepared to improve the distribution of tasks for the upcoming MIREX 2020. To do so, we really need leaders to help us organize and run each task.

To volunteer to lead a task, please complete the form [https://forms.gle/9idWhxPgdisxFW55A here]. Current information about task captains can be found on the [[2020:Task Captains]] page. Please direct any communication to the [https://lists.ischool.illinois.edu/lists/admin/evalfest EvalFest] mailing list.

What does it mean to lead a task?
* Update wiki pages as needed
* Communicate with submitters and troubleshooting submissions
* Execution and evaluation of submissions
* Publishing final results

Due to the proprietary nature of much of the data, the submission system, evaluation framework, and most of the datasets will continue to be hosted by IMIRSEL. However, we are prepared to provide access to task organizers to manage and run submissions on the IMIRSEL systems.

We really need leaders to help us!

==MIREX 2020 Deadline Dates==
* '''August 30th 2020'''
** [[2020:Audio Fingerprinting]] <TC: Chung-Che Wang>
** [[2020:Audio Classification (Train/Test) Tasks]] <TC: Yun Hao (IMIRSEL)>, including
*** Audio US Pop Genre Classification
*** Audio Latin Genre Classification
*** Audio Music Mood Classification
*** Audio Classical Composer Identification
** [[2020:Audio K-POP Mood Classification]] <TC: Yun Hao (IMIRSEL)>
** [[2020:Audio K-POP Genre Classification]] <TC: Yun Hao (IMIRSEL)>
** [[2020:Audio Tag Classification]] <TC: Emre Demir>

* '''September 6th 2020'''
** [[2020:Audio Chord Estimation]] <TC: Johan Pauwels>
** [[2020:Audio Cover Song Identification]] <TC: Yun Hao (IMIRSEL)>
** [[2020:Audio Downbeat Estimation]] <TC: Mickaël Zehren>
** [[2020:Audio Key Detection]] <TC: Johan Pauwels>
** [[2020:Audio Melody Extraction]] <TC: An-Qi Huang>
** [[2020:Patterns for Prediction]] (offshoot of [[2017:Discovery of Repeated Themes & Sections]]) <TC: Berit Janssen, Iris Ren, and Tom Collins>
** [[2020:Query by Singing/Humming]] <TC: Makarand Velankar>
** [[2020:Multiple Fundamental Frequency Estimation & Tracking]] <TC: Yun Hao (IMIRSEL)>
** [[2020:Lyrics Transcription]] (former: Automatic Lyrics-to-Audio Alignment) <TC: Georgi Dzhambazov, Daniel Stoller>

* '''September 13th 2020'''
** '''''NEW!''''' [[2020:Singing_Transcription_from_Polyphonic_Music]] <TC: Jun-You Wang>

==MIREX 2020 Submission Instructions==
* Be sure to read through the rest of this page
* Be sure to read though the task pages for which you are submitting
* Be sure to follow the [[2009:Best Coding Practices for MIREX | Best Coding Practices for MIREX]]
* Be sure to follow the [[MIREX 2020 Submission Instructions]] including both the tutorial video and the text
* The MIREX 2020 Submission System is coming soon at: https://www.music-ir.org/mirex/sub/.

==MIREX 2020 Evaluation==

===Note to New Participants===
Please take the time to read the following review articles that explain the history and structure of MIREX.

Downie, J. Stephen (2008). The Music Information Retrieval Evaluation Exchange (2005-2007): 
A window into music information retrieval research.''Acoustical Science and Technology 29'' (4): 247-255. 
Available at: [http://dx.doi.org/10.1250/ast.29.247 http://dx.doi.org/10.1250/ast.29.247]

Downie, J. Stephen, Andreas F. Ehmann, Mert Bay and M. Cameron Jones. (2010). 
The Music Information Retrieval Evaluation eXchange: Some Observations and Insights. 
''Advances in Music Information Retrieval'' Vol. 274, pp. 93-115 
Available at: [http://bit.ly/KpM5u5 http://bit.ly/KpM5u5]

===Runtime Limits===

We reserve the right to stop any process that exceeds runtime limits for each task. We will do our best to notify you in enough time to allow revisions, but this may not be possible in some cases. Please respect the published runtime limits.

===Note to All Participants===

Because MIREX is premised upon the sharing of ideas and results, '''ALL''' MIREX participants are expected to:

# submit a DRAFT 2-3 page extended abstract PDF in the ISMIR format about the submitted program(s) to help us and the community better understand how the algorithm works when submitting their programme(s).
# submit a FINALIZED 2-3 page extended abstract PDF in the ISMIR format prior to ISMIR 2020 for posting on the respective results pages (sometimes the same abstract can be used for multiple submissions; in many cases the DRAFT and FINALIZED abstracts are the same).
# present a poster at the MIREX 2020 poster session at ISMIR 2020, if there is a physical component to the conference.

===Software Dependency Requests===
If you have not submitted to MIREX before or are unsure whether IMIRSEL currently supports some of the software/architecture dependencies for your submission, please contact [mailto:yunhao2@illinois.edu IMIRSEL team] as early as possible. Failing to notify the team might result in your submission being rejected.

Finally, you will also be expected to detail your software/architecture dependencies in a README file to be provided to the submission system.

==Getting Involved in MIREX 2020==
MIREX is a community-based endeavour. Be a part of the community and help make MIREX 2020 the best yet.

===Mailing List Participation===
If you are interested in formal MIR evaluation, you should also subscribe to the "MIREX" (aka "EvalFest") mail list and participate in the community discussions about defining and running MIREX 2020 tasks. Subscription information at:
[https://mail.lis.illinois.edu/mailman/listinfo/evalfest EvalFest Central].

If you are participating in MIREX 2020, it is VERY IMPORTANT that you are subscribed to EvalFest. Deadlines, task updates and other important information will be announced via this mailing list. Please use the EvalFest for discussion of MIREX task proposals and other MIREX related issues. This wiki (MIREX 2020 wiki) will be used to embody and disseminate task proposals, however, task related discussions should be conducted on the MIREX organization mailing list (EvalFest) rather than on this wiki, but should be summarized here.

Where possible, definitions or example code for new evaluation metrics or tasks should be provided to the IMIRSEL team who will embody them in software as part of the NEMA analytics framework, which will be released to the community at or before ISMIR 2020 - providing a standardised set of interfaces and output to disciplined evaluation procedures for a great many MIR tasks.

===Wiki Participation===
If you find that you cannot edit a MIREX wiki page, you will need to create a new account via: [[Special:Userlogin]].

Please note that because of "spam-bots", MIREX wiki registration requests may be moderated by IMIRSEL members. It might take up to 24 hours for approval (Thank you for your patience!).

==MIREX 2005 - 2019 Wikis==
Content from MIREX 2005 - 2018 are available at:
'''[[2019:Main_Page|MIREX 2019]]'''
'''[[2018:Main_Page|MIREX 2018]]'''
'''[[2017:Main_Page|MIREX 2017]]'''
'''[[2016:Main_Page|MIREX 2016]]'''
'''[[2015:Main_Page|MIREX 2015]]'''
'''[[2014:Main_Page|MIREX 2014]]'''
'''[[2013:Main_Page|MIREX 2013]]'''
'''[[2012:Main_Page|MIREX 2012]]'''
'''[[2011:Main_Page|MIREX 2011]]'''
'''[[2010:Main_Page|MIREX 2010]]'''
'''[[2009:Main_Page|MIREX 2009]]'''
'''[[2008:Main_Page|MIREX 2008]]'''
'''[[2007:Main_Page|MIREX 2007]]'''
'''[[2006:Main_Page|MIREX 2006]]'''
'''[[2005:Main_Page|MIREX 2005]]'''

User:Jywang

2020-08-24T20:43:24Z

Yun Hao: Creating user page for new user.

A student of NTU(National Taiwan University) MIRLAB.

User talk:Jywang

2020-08-24T20:43:24Z

Yun Hao: Welcome!

'''Welcome to ''MIREX Wiki''!'''
We hope you will contribute much and well.
You will probably want to read the [https://www.mediawiki.org/wiki/Special:MyLanguage/Help:Contents help pages].
Again, welcome and have fun! [[User:Yun Hao|Yun Hao]] ([[User talk:Yun Hao|talk]]) 15:43, 24 August 2020 (CDT)

2020:Singing Transcription from Polyphonic Music

2020-08-19T20:56:31Z

Yun Hao: /* Reference */

== Description ==
The goal of this task is to transcribe the vocal part of polyphonic music into a series of notes, each note contains onset, offset and score pitch. The input of this task is a music recording, mostly pop music, that contains a vocal and some accompaniments. The vocal part is monophonic, but the accompaniments are not.
Therefore, to deal with this task, algorithms that separate vocal part from audio may be considered as a preprocessing step. However, this is not a necessary part of a singing transcription algorithm. Algorithms that directly perform singing transcription on mixed audio are also welcome.
This task is different from “audio melody extraction”, since the target of melody extraction is to determine pitch for each frame, while singing transcription is aimed to determine notes of vocal part in music.

== Data ==
Two datasets can be used to construct and evaluate a model for singing transcription:
=== RWC Music Database [1]: Popular Music (RWC-MDB-P) ===
We can use the “Popular Music Database” part of RWC database for this task. RWC-MDB-P consists of 100 songs and annotations in MIDI format (AIST annotation). The database is available at https://staff.aist.go.jp/m.goto/RWC-MDB/rwc-mdb-p.html, and the annotations are available at https://staff.aist.go.jp/m.goto/RWC-MDB/AIST-Annotation. By excluding 6 songs (No. 3, 5, 8, 10, 23, and 66) with multiple singers (the melody part is not monophonic), the remaining 94 songs can be used for this task.

=== Cmedia-200 dataset ===
This dataset consists of 200 Youtube links of Chinese pop songs, together with their groundtruth files of vocal transcription. We will release 100 of the dataset as the open set for training/validation, and use the other 100 as the hidden set for test.

== Evaluation ==
We will use Python package “mir_eval” [2] to evaluate the accuracy of a transcription by computing COnPOff, COnP and COn metrics described in [3]. These metrics compute the maximum number of groundtruth notes that are corrected transcribed. Each note in groundtruth can only be matched with one transcribed note, and vice versa. Three rules are utilized to determine if two notes are matched with each other:
1. The onset difference is less than the threshold (100ms in this competition).
2. The pitch difference is less than the threshold (50 cents in this competition).
3. The offset difference is less than the threshold defined by max(50ms, 0.2* duration of groundtruth note) in this competition.
Two notes should satisfy all three conditions above to be considered as “correctly transcribed” in COnPOff metric. However, COnP only requires the two notes to satisfy (1) and (2), while COn only requires the two notes to satisfy (1).
We will compute the f1-score of COnPOff, COnP and COn on each song. The final results reported are the average f1-score of the three metrics.
In fact, the COnPOff metric is the same as the evaluation metrics of “note tracking” subtask in MIREX “Multiple Fundamental Frequency Estimation & Tracking” task. The only difference is that the onset threshold is set to 100ms instead of 50ms due to the difficulty of labeling (and maybe, transcribing) onset of singing voice.
Also, we will report another metric proposed by ourselves, the “shifted COn” metric. To compute this metric, a sub-optimal algorithm is used to automatically shift the whole prediction of a song. After finding out the proper time shift, we will then compute COn metric between the shifted prediction file and the groundtruth. The result of this COn is named as “shifted COn”.

== Submission Format ==
=== Input Format ===
Sample rate: 44.1 KHz
Sample size: 16 bit
Number of channels: 2 (stereo)
Encoding: WAV

=== Output Format ===
The algorithm should output a plain text file. Each line represents a note, which contains three numbers: onset, offset and score pitch. Onset and offset are in seconds, while score pitch should be an integer MIDI number in semitones. An example output file is shown next:
0.131 0.355 64
0.355 0.896 64
0.896 1.141 62
1.888 2.333 62

Since the vocal part is monophonic, in the groundtruth, the offset of one note is always not greater than the onset of the next note, i.e., there is no note overlapping. Also, the duration of a note is always positive. That is, the offset time of a note is always larger than the onset time of the same note. We strongly suggest the submitted algorithms to follow these rules.

=== Command line calling format ===
The submitted algorithm must take as arguments a SINGLE .wav file to perform the singing transcription on as well as the full output path and filename of the output file. The ability to specify the output path and file name is essential. Denoting the input .wav file path and name as %input and the output file path and name as %output, a program called “main” could be called from the command-line as follows:

./main %input %output

=== Time limits ===
The time limit is 24 hours. In 24 hours, the algorithm should transcribe all 294 songs in RWC dataset and Cmedia dataset, of which the total duration is about 20hr.

== Reference ==
[1] Masataka Goto, Hiroki Hashiguchi, Takuichi Nishimura, and Ryuichi Oka: “RWC Music Database: Popular, Classical, and Jazz Music Databases,” Proceedings of the 3rd International Conference on Music Information Retrieval (ISMIR 2002), pp.287-288, October 2002.

[2] C. Raffel, B. McFee, E. J. Humphrey, J. Salamon, O. Nieto, D. Liang, and D. P. W. Ellis, “mir_eval: A Transparent Implementation of Common MIR Metrics,” in Proceedings of the 15th International Conference on Music Information Retrieval, 2014.

[3] E. Molina, A. M. Barbancho-Perez, L. J. Tardón, I. Barbancho-Perez: “Evaluation Framework for Automatic Singing Transcription,” in Proceedings of the 15th International Society for Music Information Retrieval Conference (ISMIR 2014), pp.567-572, October 2014.

2020:Singing Transcription from Polyphonic Music

2020-08-19T20:56:16Z

Yun Hao: Created page with "== Description == The goal of this task is to transcribe the vocal part of polyphonic music into a series of notes, each note contains onset, offset and score pitch. The input..."

== Description ==
The goal of this task is to transcribe the vocal part of polyphonic music into a series of notes, each note contains onset, offset and score pitch. The input of this task is a music recording, mostly pop music, that contains a vocal and some accompaniments. The vocal part is monophonic, but the accompaniments are not.
Therefore, to deal with this task, algorithms that separate vocal part from audio may be considered as a preprocessing step. However, this is not a necessary part of a singing transcription algorithm. Algorithms that directly perform singing transcription on mixed audio are also welcome.
This task is different from “audio melody extraction”, since the target of melody extraction is to determine pitch for each frame, while singing transcription is aimed to determine notes of vocal part in music.

== Data ==
Two datasets can be used to construct and evaluate a model for singing transcription:
=== RWC Music Database [1]: Popular Music (RWC-MDB-P) ===
We can use the “Popular Music Database” part of RWC database for this task. RWC-MDB-P consists of 100 songs and annotations in MIDI format (AIST annotation). The database is available at https://staff.aist.go.jp/m.goto/RWC-MDB/rwc-mdb-p.html, and the annotations are available at https://staff.aist.go.jp/m.goto/RWC-MDB/AIST-Annotation. By excluding 6 songs (No. 3, 5, 8, 10, 23, and 66) with multiple singers (the melody part is not monophonic), the remaining 94 songs can be used for this task.

=== Cmedia-200 dataset ===
This dataset consists of 200 Youtube links of Chinese pop songs, together with their groundtruth files of vocal transcription. We will release 100 of the dataset as the open set for training/validation, and use the other 100 as the hidden set for test.

== Evaluation ==
We will use Python package “mir_eval” [2] to evaluate the accuracy of a transcription by computing COnPOff, COnP and COn metrics described in [3]. These metrics compute the maximum number of groundtruth notes that are corrected transcribed. Each note in groundtruth can only be matched with one transcribed note, and vice versa. Three rules are utilized to determine if two notes are matched with each other:
1. The onset difference is less than the threshold (100ms in this competition).
2. The pitch difference is less than the threshold (50 cents in this competition).
3. The offset difference is less than the threshold defined by max(50ms, 0.2* duration of groundtruth note) in this competition.
Two notes should satisfy all three conditions above to be considered as “correctly transcribed” in COnPOff metric. However, COnP only requires the two notes to satisfy (1) and (2), while COn only requires the two notes to satisfy (1).
We will compute the f1-score of COnPOff, COnP and COn on each song. The final results reported are the average f1-score of the three metrics.
In fact, the COnPOff metric is the same as the evaluation metrics of “note tracking” subtask in MIREX “Multiple Fundamental Frequency Estimation & Tracking” task. The only difference is that the onset threshold is set to 100ms instead of 50ms due to the difficulty of labeling (and maybe, transcribing) onset of singing voice.
Also, we will report another metric proposed by ourselves, the “shifted COn” metric. To compute this metric, a sub-optimal algorithm is used to automatically shift the whole prediction of a song. After finding out the proper time shift, we will then compute COn metric between the shifted prediction file and the groundtruth. The result of this COn is named as “shifted COn”.

== Submission Format ==
=== Input Format ===
Sample rate: 44.1 KHz
Sample size: 16 bit
Number of channels: 2 (stereo)
Encoding: WAV

=== Output Format ===
The algorithm should output a plain text file. Each line represents a note, which contains three numbers: onset, offset and score pitch. Onset and offset are in seconds, while score pitch should be an integer MIDI number in semitones. An example output file is shown next:
0.131 0.355 64
0.355 0.896 64
0.896 1.141 62
1.888 2.333 62

Since the vocal part is monophonic, in the groundtruth, the offset of one note is always not greater than the onset of the next note, i.e., there is no note overlapping. Also, the duration of a note is always positive. That is, the offset time of a note is always larger than the onset time of the same note. We strongly suggest the submitted algorithms to follow these rules.

=== Command line calling format ===
The submitted algorithm must take as arguments a SINGLE .wav file to perform the singing transcription on as well as the full output path and filename of the output file. The ability to specify the output path and file name is essential. Denoting the input .wav file path and name as %input and the output file path and name as %output, a program called “main” could be called from the command-line as follows:

./main %input %output

=== Time limits ===
The time limit is 24 hours. In 24 hours, the algorithm should transcribe all 294 songs in RWC dataset and Cmedia dataset, of which the total duration is about 20hr.

== Reference ==
[1] Masataka Goto, Hiroki Hashiguchi, Takuichi Nishimura, and Ryuichi Oka: “RWC Music Database: Popular, Classical, and Jazz Music Databases,” Proceedings of the 3rd International Conference on Music Information Retrieval (ISMIR 2002), pp.287-288, October 2002.
[2] C. Raffel, B. McFee, E. J. Humphrey, J. Salamon, O. Nieto, D. Liang, and D. P. W. Ellis, “mir_eval: A Transparent Implementation of Common MIR Metrics,” in Proceedings of the 15th International Conference on Music Information Retrieval, 2014.
[3] E. Molina, A. M. Barbancho-Perez, L. J. Tardón, I. Barbancho-Perez: “Evaluation Framework for Automatic Singing Transcription,” in Proceedings of the 15th International Society for Music Information Retrieval Conference (ISMIR 2014), pp.567-572, October 2014.

2020:Query by Singing/Humming

2020-08-17T22:25:06Z

Yun Hao: /* Data */

== Description ==

The text of this section is copied from the 2010 page. Please add your comments and discussions for 2020.

The goal of the Query-by-Singing/Humming (QBSH) task is the evaluation of MIR systems that take as query input queries sung or hummed by real-world users. More information can be found in:

* [[2016:Query_by_Singing/Humming]]
* [[2015:Query_by_Singing/Humming]]
* [[2014:Query_by_Singing/Humming]]
* [[2013:Query_by_Singing/Humming]]
* [[2012:Query_by_Singing/Humming]]
* [[2011:Query_by_Singing/Humming]]
* [[2010:Query_by_Singing/Humming]]
* [[2009:Query_by_Singing/Humming]]
* [[2008:Query_by_Singing/Humming]]
* [[2007:Query_by_Singing/Humming]]
* [[2006:QBSH:_Query-by-Singing/Humming]]

=== Subtask 1: Classic QBSH evaluation ===
This is the classic QBSH problem where we need to find the ground-truth midi from a user's singing or humming.
* '''Queries''': human singing/humming snippets (.wav). Queries are from MIR-QBSH and IOACAS corpora described below.
* '''Database''': ground-truth and noise MIDI files(which are monophonic). Comprised of ground-truth MIDIs from MIR-QBSH corpus (48), and IOACAS corpus (106), along with a cleaned version of Essen Database(2000+ MIDIs which are not available to the participator)
* '''Output''': top-10 candidate list.
* '''Evaluation''': Top-10 hit rate (1 point is scored for a hit in the top 10 and 0 is scored otherwise).

=== Subtask 2: Variants QBSH evaluation ===
This is based on Prof. Downie's idea that queries are variants of "ground-truth" midi. In fact, this becomes more important since user-contributed singing/humming is an important part of the song database to be searched, as evidenced by the QBSH search service at [http://www.midomi.com/ www.midomi.com].
* '''Queries''': human singing/humming snippets (.wav). Queries are from Roger Jang's corpus and IOACAS corpus.
* '''Database''': human singing/humming snippets (.wav) from all available corpora (excluding the query input being searched).
* '''Output''': top-10 candidate list.
* '''Evaluation''': Top-10 hit rate (1 point is scored for a hit in the top 10 and 0 is scored otherwise).

To make algorithms able to share intermediate steps, participants are encouraged to submit separate tracker and matcher modules instead of integrated ones, which is according to Rainer Typke's suggestion. So trackers and matchers from different submissions could work together with the same pre-defined interface and thus for us it's possible to find the best combination.

== Data ==
Currently we have 2 publicly available corpora for QBSH:

* Roger Jang's [https://music-ir.org/evaluation/MIREX/data/qbsh/MIR-QBSH-corpus.tar.gz MIR-QBSH corpus] which is comprised of 4431 queries along with 48 ground-truth MIDI files. All queries are from the beginning of references. Manually labeled pitch for each recording is available.

* [https://music-ir.org/evaluation/MIREX/data/qbsh/IOACAS_QBH_Corpus.tar.gz IOACAS corpus] comprised of 759 queries and 298 monophonic ground-truth MIDI files (with MIDI 0 or 1 format). There are no "singing from beginning" guarantee.

The noise MIDI will be the 5000+ Essen collection(can be accessed from http://www.esac-data.org/).

To build a large test set which can reflect real-world queries, it is suggested that every participant makes a contribution to the evaluation corpus. Sometimes this is hard in practice. So we shall adopt "no hidden dataset" policy if there are not enough user-contributed copora.

== Evaluation Corpus Contribution ==
Every participant will be asked to contribute 100~200 wave queries (8k 16bits) as well as the ground truth MIDI as test data.

A simple tool for recording query data will be public soon. You may need to have .NET 2.0 or above installed in your system in order to run this program. The generated files conform to the format used in the IOACAS corpus. Of course you are also welcomed to use your own program to record the query data.

If there are not enough user-contributed corpora, then we shall adopt "no hidden dataset" policy for QBSH task as usual.

== Submission Format ==

=== Breakdown Version ===
1. Database indexing/building. Command format should look like this:

indexing %dbMidi.list% %dir_workspace_root%

where %dbMidi.list% is the input list of database midi files named as uniq_key.mid. For example:

./QBSH/midiDatabase/00001.mid
./QBSH/midiDatabase/00002.mid
./QBSH/midiDatabase/00003.mid
./QBSH/midiDatabase/00004.mid
...

Output indexed files are placed into %dir_workspace_root%. (For task 2, %dbMidi.list% is in fact a list of wav files in the database.)

2. Pitch tracker. Command format:

pitch_tracker %queryWave.list% %dir_query_pitch%

where %queryWave.list% looks like

queryWave/query_00001.wav
queryWave/query_00002.wav
queryWave/query_00003.wav
...

Each input file dir_query/query_xxxxx.wav in %queryWave.list% outputs a corresponding transcription %dir_query_pitch%/query_xxxxx.pitch which gives the pitch sequence in midi note scale with the resolution of 10ms:

0
0
62.23
62.25
62.21
...

Thus a query with x seconds should output a pitch file with 100*x lines. Places of silence/rest are set to be 0.

3. Pitch matcher. Command format:

pitch_matcher %dbMidi.list% %queryPitch.list% %resultFile%

where %queryPitch.list% looks like

queryPitch/query_00001.pitch
queryPitch/query_00002.pitch
queryPitch/query_00003.pitch
...

and the result file gives top-10 candidates(if has) for each query:

queryPitch/query_00001.pitch: 00025 01003 02200 ...
queryPitch/query_00002.pitch: 01547 02313 07653 ...
queryPitch/query_00003.pitch: 03142 00320 00973 ...
...

=== Integrated Version ===
If you want to pack everything together, the command format should be much simpler:

qbshProgram %dbMidi.list% %queryWave.list% %resultFile% %dir_workspace_root%

You can use %dir_workspace_root% to store any temporary indexing/database structures. The result file should have the same format as mentioned previously. (For task 2, %dbMidi.list% is in fact a list of wav files in the database to be retrieved.)

=== Packaging submissions ===
All submissions should be statically linked to all libraries (the presence of
dynamically linked libraries cannot be guarenteed).

All submissions should include a README file including the following the
information:

* Command line calling format for all executables and an example formatted set of commands
* Number of threads/cores used or whether this should be specified on the command line
* Expected memory footprint
* Expected runtime
* Any required environments (and versions), e.g. python, java, bash, matlab.

== Time and hardware limits ==
Due to the potentially high number of particpants in this and other audio tasks,
hard limits on the runtime of submissions are specified.

A hard limit of 72 hours will be imposed on runs (total feature extraction and querying times). Submissions that exceed this runtime may not receive a result.

== Potential Participants ==