Difference between revisions of "2014:Audio Music Similarity and Retrieval Results"

Latest revision as of 21:55, 4 February 2015

Introduction

These are the results for the 2014 running of the Audio Music Similarity and Retrieval task set. For background information about this task set please refer to the Audio Music Similarity and Retrieval page.

Each system was given 7000 songs chosen from IMIRSEL's "uspop", "uscrap" and "american" "classical" and "sundry" collections. Each system then returned a 7000x7000 distance matrix. 50 songs were randomly selected from the 10 genre groups (5 per genre) as queries and the first 5 most highly ranked songs out of the 7000 were extracted for each query (after filtering out the query itself, returned results from the same artist were also omitted). Then, for each query, the returned results (candidates) from all participants were grouped and were evaluated by human graders using the Evalutron 6000 grading system. Each individual query/candidate set was evaluated by a single grader. For each query/candidate pair, graders provided two scores. Graders were asked to provide 1 categorical BROAD score with 3 categories: NS,SS,VS as explained below, and one FINE score (in the range from 0 to 100). A description and analysis is provided below.

The systems read in 30 second audio clips as their raw data. The same 30 second clips were used in the grading stage.

General Legend

Team ID

Sub code	Submission name	Abstract	Contributors
FFMD1	FFMD	PDF	Peter Foster, György Fazekas, Matthias Mauch, Simon Dixon
GK1	ILSP AMS	PDF	Aggelos Gkiokas, Vassilis Katsouros, George Carayannis
GKC2	ILSP AMS 2	PDF	Aggelos Gkiokas, Vassilis Katsouros, George Carayannis
GKC3	ILSP AMS 3	PDF	Aggelos Gkiokas, Vassilis Katsouros, George Carayannis
PS1	PS09	PDF	Dominik Schnitzer, Tim Pohle
SS2	cbmr_sim_2013_resubmission	PDF	Klaus Seyerlehner, Markus Schedl
SS4	cbmr_sim_2014_submission	PDF	Klaus Seyerlehner, Markus Schedl
SS5	AM-ES	PDF	Abhinava Srivastava, Mohit Sinha

Broad Categories

NS = Not Similar
SS = Somewhat Similar
VS = Very Similar

Understanding Summary Measures

Fine = Has a range from 0 (failure) to 100 (perfection).
Broad = Has a range from 0 (failure) to 2 (perfection) as each query/candidate pair is scored with either NS=0, SS=1 or VS=2.

Human Evaluation

Overall Summary Results

Measure	FFMD1	GK1	GKC2	GKC3	PS1	SS2	SS4	SS5
Average Fine Score	38.164	35.290	35.334	34.556	48.880	49.352	49.008	45.082
Average Cat Score	0.732	0.634	0.632	0.614	1.014	1.014	1.020	0.920

download these results as csv

Friedman's Tests

Friedman's Test (FINE Scores)

The Friedman test was run in MATLAB against the Fine summary data over the 50 queries.
Command: [c,m,h,gnames] = multcompare(stats, 'ctype', 'tukey-kramer','estimate', 'friedman', 'alpha', 0.05);

TeamID	TeamID	Lowerbound	Mean	Upperbound	Significance
SS2	SS4	-1.543	-0.060	1.423	FALSE
SS2	PS1	-1.553	-0.070	1.413	FALSE
SS2	SS5	-0.853	0.630	2.113	FALSE
SS2	FFMD1	0.927	2.410	3.893	TRUE
SS2	GKC2	1.557	3.040	4.523	TRUE
SS2	GK1	1.137	2.620	4.103	TRUE
SS2	GKC3	1.627	3.110	4.593	TRUE
SS4	PS1	-1.493	-0.010	1.473	FALSE
SS4	SS5	-0.793	0.690	2.173	FALSE
SS4	FFMD1	0.987	2.470	3.953	TRUE
SS4	GKC2	1.617	3.100	4.583	TRUE
SS4	GK1	1.197	2.680	4.163	TRUE
SS4	GKC3	1.687	3.170	4.653	TRUE
PS1	SS5	-0.783	0.700	2.183	FALSE
PS1	FFMD1	0.997	2.480	3.963	TRUE
PS1	GKC2	1.627	3.110	4.593	TRUE
PS1	GK1	1.207	2.690	4.173	TRUE
PS1	GKC3	1.697	3.180	4.663	TRUE
SS5	FFMD1	0.297	1.780	3.263	TRUE
SS5	GKC2	0.927	2.410	3.893	TRUE
SS5	GK1	0.507	1.990	3.473	TRUE
SS5	GKC3	0.997	2.480	3.963	TRUE
FFMD1	GKC2	-0.853	0.630	2.113	FALSE
FFMD1	GK1	-1.273	0.210	1.693	FALSE
FFMD1	GKC3	-0.783	0.700	2.183	FALSE
GKC2	GK1	-1.903	-0.420	1.063	FALSE
GKC2	GKC3	-1.413	0.070	1.553	FALSE
GK1	GKC3	-0.993	0.490	1.973	FALSE

download these results as csv

Friedman's Test (BROAD Scores)

The Friedman test was run in MATLAB against the BROAD summary data over the 50 queries.
Command: [c,m,h,gnames] = multcompare(stats, 'ctype', 'tukey-kramer','estimate', 'friedman', 'alpha', 0.05);

TeamID	TeamID	Lowerbound	Mean	Upperbound	Significance
SS4	PS1	-1.492	-0.060	1.372	FALSE
SS4	SS2	-1.342	0.090	1.522	FALSE
SS4	SS5	-1.182	0.250	1.682	FALSE
SS4	FFMD1	0.518	1.950	3.382	TRUE
SS4	GK1	1.128	2.560	3.992	TRUE
SS4	GKC2	1.328	2.760	4.192	TRUE
SS4	GKC3	1.418	2.850	4.282	TRUE
PS1	SS2	-1.282	0.150	1.582	FALSE
PS1	SS5	-1.122	0.310	1.742	FALSE
PS1	FFMD1	0.578	2.010	3.442	TRUE
PS1	GK1	1.188	2.620	4.052	TRUE
PS1	GKC2	1.388	2.820	4.252	TRUE
PS1	GKC3	1.478	2.910	4.342	TRUE
SS2	SS5	-1.272	0.160	1.592	FALSE
SS2	FFMD1	0.428	1.860	3.292	TRUE
SS2	GK1	1.038	2.470	3.902	TRUE
SS2	GKC2	1.238	2.670	4.102	TRUE
SS2	GKC3	1.328	2.760	4.192	TRUE
SS5	FFMD1	0.268	1.700	3.132	TRUE
SS5	GK1	0.878	2.310	3.742	TRUE
SS5	GKC2	1.078	2.510	3.942	TRUE
SS5	GKC3	1.168	2.600	4.032	TRUE
FFMD1	GK1	-0.822	0.610	2.042	FALSE
FFMD1	GKC2	-0.622	0.810	2.242	FALSE
FFMD1	GKC3	-0.532	0.900	2.332	FALSE
GK1	GKC2	-1.232	0.200	1.632	FALSE
GK1	GKC3	-1.142	0.290	1.722	FALSE
GKC2	GKC3	-1.342	0.090	1.522	FALSE

download these results as csv

Summary Results by Query

FINE Scores

These are the mean FINE scores per query assigned by Evalutron graders. The FINE scores for the 5 candidates returned per algorithm, per query, have been averaged. Values are bounded between 0 and 100. A perfect score would be 100. Genre labels have been included for reference.

Genre	Query	FFMD1	GK1	GKC2	GKC3	PS1	SS2	SS4	SS5
BAROQUE	d001397	56.7	25.7	18.1	5.8	62.5	70.2	67.3	65.9
BAROQUE	d001459	37.7	2	23.4	32.2	85.7	89.2	93.3	88.7
BAROQUE	d002624	67.4	54.7	49.4	40.6	85.9	84.6	83.8	83.8
BAROQUE	d015486	66.2	73.1	66.4	65.1	82.3	81.2	81.5	82.5
BAROQUE	d019963	73.9	69.3	68.9	66.1	85.4	81.1	83.1	84.4
BLUES	e002382	48.7	44.7	41.7	40.5	41.0	49.0	47.4	44.0
BLUES	e004484	59.4	59.6	52.7	53.7	68.9	59.4	69.0	59.4
BLUES	e006191	63.1	45.0	44.6	40.1	62.8	65.9	68.3	62.9
BLUES	e008309	31.5	36.8	39.6	39.6	56.1	43.1	40.0	51.7
BLUES	e017534	42.5	45.5	45.6	45.1	55.2	52.4	52.7	43.9
CLASSICAL	d002003	15.5	10.7	1	1	20.7	7.9	2.6	13.0
CLASSICAL	d007289	91.2	44.3	67.6	52.8	95.8	95.5	96.2	95.9
CLASSICAL	d011638	2.7	5.6	3.1	3.1	37.5	26.9	19.0	29.8
CLASSICAL	d012026	1.6	11.2	12.8	13.5	21.9	22.3	25.2	20.1
CLASSICAL	d016699	25.2	23.3	26.2	26.0	28.8	31.0	26.7	31.5
COUNTRY	e001114	47.5	36.0	46.5	53.0	58.0	45.0	47.5	67.0
COUNTRY	e008446	45.5	57.6	60.5	58.6	51.4	54.0	64.1	49.8
COUNTRY	e009159	11.1	36.7	31.4	26.3	51.0	33.0	32.4	39.8
COUNTRY	e016660	28.1	18.3	19.9	13.2	22.9	29.4	20.6	20.9
COUNTRY	e018065	22.0	25.4	27.4	31.9	45.0	36.2	42.2	44.1
EDANCE	a005631	35.9	22.6	30.1	26.6	54.1	44.8	39.5	41.2
EDANCE	a005956	19.3	14.3	12.9	12.7	33.6	42.2	45.9	25.1
EDANCE	b001277	15.0	34.9	28.8	37.2	29.5	50.0	43.8	14.5
EDANCE	f001351	51.8	56.5	55.0	53.0	35.9	56.0	60.1	27.4
EDANCE	f013763	53.2	25.1	30.0	26.1	32.6	45.4	47.6	35.7
JAZZ	e004761	39.7	29.8	44.3	35.8	24.6	51.4	51.6	32.0
JAZZ	e008457	31.1	23.3	30.7	35.0	51.6	61.1	53.3	40.7
JAZZ	e017361	51.4	31.8	39.7	44.0	53.2	52.0	52.9	31.1
JAZZ	e018523	5.8	21.4	21.8	21.8	18.4	37.2	37.6	32.5
JAZZ	e018792	38.4	49.1	37.4	43.5	44.2	40.6	39.2	39.4
METAL	a005951	24.7	44.0	46.7	46.6	54.0	30.5	31.4	37.3
METAL	b001596	28.9	56.5	43.0	52.7	70.3	72.8	71.6	37.5
METAL	b018086	16.6	27.8	25.4	26.3	32.0	24.0	21.6	28.0
METAL	b018190	14.1	16.9	19.7	18.8	26.3	27.3	25.7	25.6
METAL	b019401	9	7	6.6	10.5	5.9	11.6	10.1	15.8
RAPHIPHOP	a000917	76.6	63.2	61.3	61.2	81.1	79.6	79.0	64.9
RAPHIPHOP	a002493	72.5	74.5	58.5	70.5	74.5	77.0	77.5	78.0
RAPHIPHOP	a004652	57.9	53.0	51.9	54.6	52.0	68.3	51.4	56.2
RAPHIPHOP	a008454	4.9	9.7	14.7	12.2	21.3	9.6	10.7	21.2
RAPHIPHOP	b019567	1.9	2.3	0.8	1	2.1	8	5	5.8
ROCKROLL	b006054	32.9	25.5	21.9	24.1	35.2	30.2	32.1	26.5
ROCKROLL	b011339	47.1	42.2	40.6	41.9	48.9	57.8	55.0	44.1
ROCKROLL	b012144	45.8	38.6	41.1	42.6	49.2	40.9	47.5	45.1
ROCKROLL	b016472	41.3	17.3	16.8	10.6	66.4	47.3	52.7	47.9
ROCKROLL	b017328	47.0	35.0	34.0	33.0	54.5	57.5	52.0	56.0
ROMANTIC	d001837	29.8	44.8	43.9	42.9	55.6	61.8	69.3	49.6
ROMANTIC	d004789	24.4	6.5	7.3	6.3	23.8	22.0	24.3	25.9
ROMANTIC	d009318	30.5	48.5	41.0	16.0	67.5	66.0	69.5	66.5
ROMANTIC	d014202	53.8	47.9	48.3	47.9	56.7	70.4	62.9	54.7
ROMANTIC	d015836	69.4	69.0	65.7	64.2	70.2	67.0	66.7	68.8

download these results as csv

BROAD Scores

These are the mean BROAD scores per query assigned by Evalutron graders. The BROAD scores for the 5 candidates returned per algorithm, per query, have been averaged. Values are bounded between 0 (not similar) and 2 (very similar). A perfect score would be 2. Genre labels have been included for reference.

Genre	Query	FFMD1	GK1	GKC2	GKC3	PS1	SS2	SS4	SS5
BAROQUE	d001397	1	0.4	0.3	0	1.2	1.2	1.2	1.3
BAROQUE	d001459	0.7	0	0.4	0.6	1.8	2	2	1.9
BAROQUE	d002624	1.3	0.7	0.6	0.3	1.8	1.8	1.7	1.7
BAROQUE	d015486	1.3	1.6	1.4	1.3	2	2	2	2
BAROQUE	d019963	2	1.7	1.7	1.6	2	2	2	2
BLUES	e002382	0.9	0.9	0.9	0.7	0.7	0.9	0.9	1
BLUES	e004484	1.4	1.1	1.1	1.1	1.8	1.4	1.7	1.4
BLUES	e006191	1.4	0.8	0.8	0.6	1.3	1.5	1.6	1.3
BLUES	e008309	0.6	0.7	0.8	0.8	1.4	1	0.8	1.1
BLUES	e017534	0.8	0.9	0.9	0.9	1.1	1	1.1	0.8
CLASSICAL	d002003	0.3	0.2	0	0	0.4	0.1	0	0.3
CLASSICAL	d007289	2	0.8	1.4	1	2	2	2	2
CLASSICAL	d011638	0.1	0.1	0.1	0.1	1	0.8	0.8	0.8
CLASSICAL	d012026	0	0.4	0.3	0.4	0.8	0.7	0.8	0.8
CLASSICAL	d016699	0.4	0.3	0.4	0.4	0.3	0.3	0.2	0.5
COUNTRY	e001114	0.6	0.6	0.6	0.8	1.1	0.5	0.7	1.5
COUNTRY	e008446	0.9	1.2	1.3	1.3	1	1.1	1.5	1.1
COUNTRY	e009159	0	0.7	0.6	0.5	1.4	0.6	0.6	0.9
COUNTRY	e016660	0.6	0.1	0.2	0.1	0.2	0.6	0.2	0.3
COUNTRY	e018065	0.4	0.3	0.3	0.5	0.7	0.7	0.6	0.7
EDANCE	a005631	0.6	0.2	0.5	0.4	1	0.8	0.7	0.8
EDANCE	a005956	0.1	0.1	0	0	0.5	0.8	0.9	0.3
EDANCE	b001277	0.1	0.6	0.5	0.6	0.3	1	1	0.2
EDANCE	f001351	1	1.1	1.1	1.1	0.5	1	1.1	0.3
EDANCE	f013763	1.1	0.5	0.6	0.6	0.5	0.9	0.9	0.7
JAZZ	e004761	0.8	0.5	0.8	0.6	0.3	1.2	1.2	0.4
JAZZ	e008457	0.8	0.5	0.8	1	1.5	1.4	1.4	1
JAZZ	e017361	0.7	0.4	0.5	0.6	1	0.9	0.8	0.2
JAZZ	e018523	0.2	0.7	0.6	0.6	0.5	1	1.1	0.9
JAZZ	e018792	0.6	0.5	0.5	0.4	0.8	0.6	0.8	0.7
METAL	a005951	0.3	0.7	0.9	0.8	1.3	0.3	0.4	0.6
METAL	b001596	0.4	1.3	0.8	1.1	1.7	1.7	1.6	0.6
METAL	b018086	0	0.5	0.4	0.4	0.5	0.3	0.2	0.4
METAL	b018190	0.1	0.3	0.3	0.3	0.4	0.4	0.4	0.4
METAL	b019401	0.1	0.1	0	0.1	0.1	0.2	0.2	0.3
RAPHIPHOP	a000917	1.8	1.4	1.3	1.3	2	2	2	1.6
RAPHIPHOP	a002493	1.5	1.5	1	1.5	1.7	1.6	1.5	1.7
RAPHIPHOP	a004652	1.3	1	1	1	1.1	1.5	1.1	1.2
RAPHIPHOP	a008454	0.1	0.3	0.4	0.3	0.5	0.1	0.2	0.5
RAPHIPHOP	b019567	0.1	0	0	0	0	0.2	0.1	0.2
ROCKROLL	b006054	0.6	0.4	0.3	0.4	0.7	0.4	0.4	0.6
ROCKROLL	b011339	0.9	0.8	0.7	0.7	0.7	1.3	1.3	0.8
ROCKROLL	b012144	0.6	0.2	0.3	0.3	0.7	0.3	0.6	0.5
ROCKROLL	b016472	0.9	0.2	0.2	0.1	1.4	1.1	1.3	1
ROCKROLL	b017328	0.7	0.4	0.3	0.3	1	1.2	0.8	1.1
ROMANTIC	d001837	0.4	0.8	0.7	0.7	1.2	1.4	1.7	0.9
ROMANTIC	d004789	0.8	0.2	0.2	0.2	1	0.8	0.8	1
ROMANTIC	d009318	0.4	0.6	0.5	0	0.9	1	1.1	1.1
ROMANTIC	d014202	1.2	0.9	0.9	0.9	1.2	1.6	1.4	1
ROMANTIC	d015836	1.7	1.5	1.4	1.4	1.7	1.5	1.6	1.6

download these results as csv

Raw Scores

The raw data derived from the Evalutron 6000 human evaluations are located on the 2014:Audio Music Similarity and Retrieval Raw Data page.

Metadata and Distance Space Evaluation

The following reports provide evaluation statistics based on analysis of the distance space and metadata matches and include:

Neighbourhood clustering by artist, album and genre
Artist-filtered genre clustering
How often the triangular inequality holds
Statistics on 'hubs' (tracks similar to many tracks) and orphans (tracks that are not similar to any other tracks at N results).

Reports

FFMD1 = Peter Foster, György Fazekas, Matthias Mauch, Simon Dixon
GK1 = Aggelos Gkiokas, Vassilis Katsouros, George Carayannis
GKC2 = Aggelos Gkiokas, Vassilis Katsouros, George Carayannis
GKC3 = Aggelos Gkiokas, Vassilis Katsouros, George Carayannis
PS1 = Tim Pohle, Dominik Schnitzer
SS2 = Klaus Seyerlehner, Markus Schedl
SS4 = Klaus Seyerlehner, Markus Schedl
SS5 = Abhinava Srivastava, Mohit Sinha

@@ Line 1: / Line 1: @@
 == Introduction ==
-These are the results for the 2013 running of the Audio Music Similarity and Retrieval task set. For background information about this task set please refer to the Audio Music Similarity and Retrieval page.
+These are the results for the 2014 running of the Audio Music Similarity and Retrieval task set. For background information about this task set please refer to the Audio Music Similarity and Retrieval page.
 Each system was given 7000 songs chosen from IMIRSEL's "uspop", "uscrap" and "american" "classical" and "sundry" collections. Each system then returned a 7000x7000 distance matrix. 50 songs were randomly selected from the 10 genre groups (5 per genre) as queries and the first 5 most highly ranked songs out of the 7000 were extracted for each query (after filtering out the query itself, returned results from the same artist were also omitted). Then, for each query, the returned results (candidates) from all participants were grouped and were evaluated by human graders using the Evalutron 6000 grading system. Each individual query/candidate set was evaluated by a single grader. For each query/candidate pair, graders provided two scores. Graders were asked to provide 1 categorical '''BROAD''' score with 3 categories: NS,SS,VS as explained below, and one '''FINE''' score (in the range from 0 to 100). A description and analysis is provided below.
@@ Line 18: / Line 18: @@
 	! width="440" | Contributors
 	|-
-         ! DM1
+         ! FFMD1
-	| DM1 ||  style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2013/DM1.pdf PDF] || [http://www.iam.ecs.soton.ac.uk/ Franz	de Leon], [http://www.iam.ecs.soton.ac.uk/ Kirk	Martinez]
+	| FFMD ||  style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2014/FFMD1.pdf PDF] || [http://www.eecs.qmul.ac.uk/~peterf/ Peter Foster], [http://c4dm.eecs.qmul.ac.uk/people/gyorgyf.htm György Fazekas], [http://www.eecs.qmul.ac.uk/people/view/2932/dr-matthias-mauch Matthias Mauch], [http://www.eecs.qmul.ac.uk/~simond/ Simon Dixon]
          |-
-         ! DM2
+         ! GK1
-	| DM2 ||  style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2013/DM3.pdf PDF] || [http://www.iam.ecs.soton.ac.uk/ Franz	de Leon], [http://www.iam.ecs.soton.ac.uk/ Kirk	Martinez]
+	| ILSP AMS ||  style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2014/GK1.pdf PDF] ||  [http://www.ilsp.gr/en/infoprojects/meta?view=member&task=show&id=20 Aggelos Gkiokas], [http://www.ilsp.gr/en/research/publications?view=member&id=33&task=show Vassilis Katsouros], [http://www.ilsp.gr/homepages/carayannis_eng.html George Carayannis]
 	|-
-         ! GKC1
+         ! GKC2
-	| ILSP Audio Similarity ||  style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2013/GKC1.pdf PDF] || [http://www.ilsp.gr/ Aggelos Gkiokas], [http://www.ilsp.gr/ Vassilis Katsouros], [http://www.ece.ntua.gr/index.php?option=com_dep&task=profile&id=12&Itemid=62&lang=en George Carayannis]
+	| ILSP AMS 2 ||  style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2014/GKC2.pdf PDF] ||  [http://www.ilsp.gr/en/infoprojects/meta?view=member&task=show&id=20 Aggelos Gkiokas], [http://www.ilsp.gr/en/research/publications?view=member&id=33&task=show Vassilis Katsouros], [http://www.ilsp.gr/homepages/carayannis_eng.html George Carayannis]
          |-
-         ! GKC2
+         ! GKC3
-	| ILSP Audio Similarity 2 ||  style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2013/GKC2.pdf PDF] || [http://www.ilsp.gr/en/infoprojects/meta?view=member&task=show&id=20 Aggelos Gkiokas], [http://www.ilsp.gr/en/research/publications?view=member&id=33&task=show Vassilis Katsouros], [http://www.ilsp.gr/homepages/carayannis_eng.html George Carayannis]
+	| ILSP AMS 3 ||  style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2014/GKC3.pdf PDF] || [http://www.ilsp.gr/en/infoprojects/meta?view=member&task=show&id=20 Aggelos Gkiokas], [http://www.ilsp.gr/en/research/publications?view=member&id=33&task=show Vassilis Katsouros], [http://www.ilsp.gr/homepages/carayannis_eng.html George Carayannis]
          |-
          ! PS1
 	| PS09 ||  style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2011/PS1.pdf PDF] || [http://www.ofai.at/~dominik.schnitzer Dominik Schnitzer], [http://www.cp.jku.at/ Tim Pohle]
          |-
-         ! RA1
+         ! SS2
-	| SimRet2013 ||  style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2013/RA1.pdf PDF] || [http://www.bsu.by/en/main.aspx Roman Aliyev]
+	| cbmr_sim_2013_resubmission ||  style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2014/SS2.pdf PDF] || [http://www.seyerlehner.info Klaus Seyerlehner], [http://www.cp.jku.at Markus Schedl]
          |-
-         ! SS2
+         ! SS4
-	| cbmr_sim_2013_submission ||  style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2013/SS2.pdf PDF] || [http://www.seyerlehner.info Klaus Seyerlehner], [http://www.cp.jku.at Markus Schedl]
+	| cbmr_sim_2014_submission ||  style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2014/SS4.pdf PDF] || [http://www.seyerlehner.info Klaus Seyerlehner], [http://www.cp.jku.at Markus Schedl]
          |-
-         ! SSPK1
+         ! SS5
-	| cbmr_sim_2010_resubmission ||  style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2012/SSKS2.pdf PDF] || [http://www.seyerlehner.info Klaus Seyerlehner], [http://www.cp.jku.at Markus Schedl], [http://www.cp.jku.at/ Tim Pohle], [http://www.cp.jku.at Peter Knees]
+	| AM-ES ||  style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2014/SS5.pdf PDF] || Abhinava Srivastava, Mohit Sinha
          |-
 	|}
@@ Line 56: / Line 56: @@
 ===Overall Summary Results===
-<csv p=3>2013/ams/2013_summary_evalutron.csv</csv>
+<csv p=3>2014/ams/2014_summary_evalutron.csv</csv>
 ===Friedman's Tests===
@@ Line 63: / Line 63: @@
 Command: [c,m,h,gnames] = multcompare(stats, 'ctype', 'tukey-kramer','estimate', 'friedman', 'alpha', 0.05);
-<csv p=3>2013/ams/2013_evalutron.fine.friedman.tukeyKramerHSD.csv</csv>
+<csv p=3>2014/ams/2014_evalutron.fine.friedman.tukeyKramerHSD.csv</csv>
-[[File:2013_evalutron.fine.friedman.tukeyKramerHSD.png|500px]]
+[[File:2014_evalutron.fine.friedman.tukeyKramerHSD.png|500px]]
 ====Friedman's Test (BROAD Scores)====
@@ Line 71: / Line 71: @@
 Command: [c,m,h,gnames] = multcompare(stats, 'ctype', 'tukey-kramer','estimate', 'friedman', 'alpha', 0.05);
-<csv p=3>2013/ams/2013_evalutron.cat.friedman.tukeyKramerHSD.csv</csv>
+<csv p=3>2014/ams/2014_evalutron.cat.friedman.tukeyKramerHSD.csv</csv>
-[[File:2013_evalutron.cat.friedman.tukeyKramerHSD.png|500px]]
+[[File:2014_evalutron.cat.friedman.tukeyKramerHSD.png|500px]]
 ===Summary Results by Query===
@@ Line 79: / Line 79: @@
 These are the mean FINE scores per query assigned by Evalutron graders. The FINE scores for the 5 candidates returned per algorithm, per query, have been averaged. Values are bounded between 0 and 100. A perfect score would be 100. Genre labels have been included for reference.
-<csv p=1>2013/ams/2013_fine_scores.csv</csv>
+<csv p=1>2014/ams/2014_fine_scores.csv</csv>
 ====BROAD Scores====
 These are the mean BROAD scores per query assigned by Evalutron graders. The BROAD scores for the 5 candidates returned per algorithm, per query, have been averaged. Values are bounded between 0 (not similar) and 2 (very similar). A perfect score would be 2. Genre labels have been included for reference.
-<csv p=1>2013/ams/2013_cat_scores.csv</csv>
+<csv p=1>2014/ams/2014_cat_scores.csv</csv>
 ===Raw Scores===
-The raw data derived from the Evalutron 6000 human evaluations are located on the [[2013:Audio Music Similarity and Retrieval Raw Data]] page.
+The raw data derived from the Evalutron 6000 human evaluations are located on the [[2014:Audio Music Similarity and Retrieval Raw Data]] page.
 ==Metadata and Distance Space Evaluation==
@@ Line 98: / Line 98: @@
 === Reports ===
-'''DM1''' = [https://music-ir.org/mirex/results/2013/ams/statistics/DM1/report.txt Franz de Leon, Kirk Martinez]<br />
+'''FFMD1''' = [https://music-ir.org/mirex/results/2014/ams/statsReports/FFMD1/report.txt Peter Foster, György Fazekas, Matthias Mauch, Simon Dixon]<br />
-'''DM2''' = [https://music-ir.org/mirex/results/2013/ams/statistics/DM2/report.txt Franz de Leon, Kirk Martinez]<br />
+'''GK1''' = [https://music-ir.org/mirex/results/2014/ams/statsReports/GK1/report.txt Aggelos Gkiokas, Vassilis Katsouros, George Carayannis]<br />
-'''GKC1''' = [https://music-ir.org/mirex/results/2013/ams/statistics/GKC1/report.txt Aggelos Gkiokas, Vassilis Katsouros, George Carayannis]<br />
+'''GKC2''' = [https://music-ir.org/mirex/results/2014/ams/statsReports/GKC2/report.txt Aggelos Gkiokas, Vassilis Katsouros, George Carayannis]<br />
-'''GKC2''' = [https://music-ir.org/mirex/results/2013/ams/statistics/GKC2/report.txt Aggelos Gkiokas, Vassilis Katsouros, George Carayannis]<br />
+'''GKC3''' = [https://music-ir.org/mirex/results/2014/ams/statsReports/GKC3/report.txt Aggelos Gkiokas, Vassilis Katsouros, George Carayannis]<br />
-'''PS1''' = [https://music-ir.org/mirex/results/2013/ams/statistics/PS1/report.txt Dominik Schnitzer, Tim Pohle]<br />
+'''PS1''' = [https://music-ir.org/mirex/results/2014/ams/statsReports/PS1/report.txt Tim Pohle, Dominik Schnitzer]<br />
-'''RA1''' = [https://music-ir.org/mirex/results/2013/ams/statistics/RA1/report.txt Roman Aliyev]<br />
+'''SS2''' = [https://music-ir.org/mirex/results/2014/ams/statsReports/SS2/report.txt Klaus Seyerlehner, Markus Schedl]<br />
-'''SS2''' = [https://music-ir.org/mirex/results/2013/ams/statistics/SS2/report.txt Klaus Seyerlehner, Markus Schedl]<br />
+'''SS4''' = [https://music-ir.org/mirex/results/2014/ams/statsReports/SS4/report.txt Klaus Seyerlehner, Markus Schedl]<br />
-'''SSPK1''' = [https://music-ir.org/mirex/results/2013/ams/statistics/SSPK1/report.txt Klaus Seyerlehner, Markus Schedl, Tim Pohle, Peter Knees]<br />
+'''SS5''' = [https://music-ir.org/mirex/results/2014/ams/statsReports/SS5/report.txt Abhinava Srivastava, Mohit Sinha]<br />

Difference between revisions of "2014:Audio Music Similarity and Retrieval Results"

Latest revision as of 21:55, 4 February 2015

Contents

Introduction

General Legend

Team ID

Broad Categories

Understanding Summary Measures

Human Evaluation

Overall Summary Results

Friedman's Tests

Friedman's Test (FINE Scores)

Friedman's Test (BROAD Scores)

Summary Results by Query

FINE Scores

BROAD Scores

Raw Scores

Metadata and Distance Space Evaluation

Reports

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