Difference between revisions of "2018:Music and or Speech Detection Results"

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! DD1
 
! DD1
| 0.2877 || 0.093 || 0.312 || 0.1142
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| 0.415 || 0.1603 || 0.4477 || 0.2122
 
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! JHKK3
 
! JHKK3
| 0.2303 || 0.0765 || 0.294 || 0.1173
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| 0.2882 || 0.0777 || 0.3289 || 0.0962
 
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! LN1
 
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| 0.1348 || 0.0139 || 0.1704 || 0.0231
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| 0.2686 || 0.0529 || 0.3484 || 0.0883
 
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! MM1
 
! MM1
| 0.2044 || 0.0662 || 0.2137 || 0.0831
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| 0.4607 || 0.2068 || 0.4898 || 0.2336
 
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! MM2
 
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| 0.2464 || 0.0817 || 0.2736 || 0.1049
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| 0.4422 || 0.1999 || 0.5093 || 0.266
 
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! MM3
 
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| 0.1379 || 0.0525 || 0.1619 || 0.0676
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| 0.4439 || 0.1775 || 0.4879 || 0.2122
 
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Revision as of 10:10, 17 September 2018

Introduction

These are the results for the 2018 running of the Music and/or Speech Detection tasks. For background information about this task set please refer to the 2018:Music and/or Speech Detection page.

General Legend

Sub code Abstract Contributors
DD1 PDF David Doukhan
JHKK1 PDF Byeong-Yong Jang, Woon-Haeng Heo, Jung-Hyun Kim, Oh-Wook Kwon
JHKK2 PDF Byeong-Yong Jang, Woon-Haeng Heo, Jung-Hyun Kim, Oh-Wook Kwon
JHKK3 PDF Byeong-Yong Jang, Woon-Haeng Heo, Jung-Hyun Kim, Oh-Wook Kwon
LN1 PDF Minsuk Choi, Jongpil Lee, Juhan Nam
MM1 PDF Matija Marolt
MM2 PDF Matija Marolt
MM3 PDF Matija Marolt
MMG1 PDF Blai Meléndez-Catalán, Emilio Molina, Emilia Gómez
MMG2 PDF Blai Meléndez-Catalán, Emilio Molina, Emilia Gómez

Task 1: Music Detection

Dataset 1

Segment-level Evaluation

Sub code Accuracy Music_F No-Music_F
DD1 0.6860 0.5424 0.7611
JHKK1 0.7798 0.7123 0.8215
JHKK2 0.8005 0.7415 0.8375
LN1 0.6251 0.5022 0.6987
MM1 0.6135 0.3899 0.7172
MM2 0.6807 0.5478 0.7531
MM3 0.6075 0.3124 0.7254
MMG1 0.9049 0.8996 0.9097

Event-level Evaluation

Sub code Music_F_500_on Music_F_500_onoff Music_F_1000_on Music_F_1000_onoff
DD1 0.2877 0.093 0.312 0.1142
JHKK1 0.2303 0.0765 0.294 0.1173
JHKK2 0.2522 0.0931 0.3245 0.1389
LN1 0.1348 0.0139 0.1704 0.0231
MM1 0.2044 0.0662 0.2137 0.0831
MM2 0.2464 0.0817 0.2736 0.1049
MM3 0.1379 0.0525 0.1619 0.0676
MMG1 0.5177 0.2693 0.5813 0.3502

Notes on metrics:

Music_F = segment-level F-measure for the music class

No-Music_F = segment-level F-measure for the no-music class

Music_F_500_on = onset-only event-level F-measure (500 ms tolerance) for the music class

Music_F_500_onoff = onset-offset event-level F-measure (500 ms tolerance) for the music class

Music_F_1000_on = onset-only event-level F-measure (1000 ms tolerance) for the music class

Music_F_1000_onoff = onset-offset event-level F-measure (1000 ms tolerance) for the music class

Task 2: Speech Detection

Segment-level Evaluation

Dataset 1

Sub code Accuracy Speech F-measure No-Speech F-measure
DD1 0.877 0.9186 0.7493
JHKK3 0.8307 0.8795 0.7143
LN1 0.6908 0.7472 0.6007
MM1 0.8626 0.9115 0.6948
MM2 0.8619 0.909 0.713
MM3 0.8508 0.9086 0.5966
LN1 0.6908 0.7472 0.6007

Event-level Evaluation

Sub code Speech_F_500_on Speech_F_500_onoff Speech_F_1000_on Speech_F_1000_onoff
DD1 0.415 0.1603 0.4477 0.2122
JHKK3 0.2882 0.0777 0.3289 0.0962
LN1 0.2686 0.0529 0.3484 0.0883
MM1 0.4607 0.2068 0.4898 0.2336
MM2 0.4422 0.1999 0.5093 0.266
MM3 0.4439 0.1775 0.4879 0.2122

Notes on metrics:

Speech_F = segment-level F-measure for the speech class

No-Speech_F = segment-level F-measure for the no-speech class

Speech_F_500_on = onset-only event-level F-measure (500 ms tolerance) for the speech class

Speech_F_500_onoff = onset-offset event-level F-measure (500 ms tolerance) for the speech class

Speech_F_1000_on = onset-only event-level F-measure (1000 ms tolerance) for the speech class

Speech_F_1000_onoff = onset-offset event-level F-measure (1000 ms tolerance) for the speech class