Difference between revisions of "2019:Automatic Lyrics-to-Audio Alignment Results"

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     ! CW1
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     ! ED1
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     | HMM-based Alignment subtask1 ||  style="text-align: center;" | [PDF not provided] || [mailto:chungchewang@kkbox.com Chung-Che Wang]
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     | Audio2Lyrics_emirdemirel ||  style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2019/ED1.pdf PDF] || [http://www.eecs.qmul.ac.uk/profiles/demirelemir.html Emir Demirel]
 
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     |-
  
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     ! CW2
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     ! GYL1
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     | HMM-based Alignment monophone acoustic models subtask2 ||  style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2018/CW2.pdf PDF] || [mailto:chungchewang@kkbox.com Chung-Che Wang]
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     | NUS ||  style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2019/GYL1.pdf PDF] || [https://www.comp.nus.edu.sg/~chitrale/ Chitralekha Gupta], [http://ece.nus.edu.sg/drupal/?q=node/159 Haizhou Li], [https://sites.google.com/site/schemreier/ Emre Yilmaz]
 
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     |-
  
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     ! CW3
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     ! JH1
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     | HMM-based Alignment bi-phone acoustic models subtask2 ||  style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2018/CW3.pdf PDF] || [mailto:chungchewang@kkbox.com Chung-Che Wang]
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     | Force Alignment with Kaldi ||  style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2019/JH1.pdf PDF] || [http://mirlab.org/jang Jyh-Shing Roger Jang], [http://mirlab.org/users/hsiangyu.huang/ Huang Hsiang-Yu]
 
     |-
 
     |-
  
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     ! GSLW1
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     ! LJ2
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     | GMM-HMM (SAT) Models subtask2 ||  style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2018/GSLW1.pdf PDF] || [mailto:chitralekha@u.nus.edu Chitralekha Gupta],  [mailto:s.bidisha@nus.edu.sg Bidisha Sharma], [mailto:haizhou.li@nus.edu.sg Haizhou Li], [mailto:dcswangy@nus.edu.sg Ye Wang]
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     | Force Alignment with Kaldi ||  style="text-align: center;" | [https://www.music-ir.org/mirex/abstracts/2019/LJ2.pdf PDF] || [http://mirlab.org/users/eddie.lin/ Chuan You Lin],  [http://mirlab.org/jang Jyh-Shing Roger Jang], [http://mirlab.org/users/hsiangyu.huang/ Huang Hsiang-Yu]
 
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     |-
−
 
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    ! GSLW2
 
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    | SAT+DNN Models subtask2  ||  style="text-align: center;" |  [https://www.music-ir.org/mirex/abstracts/2018/GSLW2.pdf PDF] || [mailto:chitralekha@u.nus.edu Chitralekha Gupta],  [mailto:s.bidisha@nus.edu.sg Bidisha Sharma], [mailto:haizhou.li@nus.edu.sg Haizhou Li], [mailto:dcswangy@nus.edu.sg Ye Wang]
 
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    |-
 
−
 
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    ! GSLW3
 
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    | Non-vocal suppression and SAT Models subtask 2  ||  style="text-align: center;" |  [https://www.music-ir.org/mirex/abstracts/2018/GSLW3.pdf PDF] || [mailto:chitralekha@u.nus.edu Chitralekha Gupta],  [mailto:s.bidisha@nus.edu.sg Bidisha Sharma], [mailto:haizhou.li@nus.edu.sg Haizhou Li], [mailto:dcswangy@nus.edu.sg Ye Wang]
 
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    |-
 
−
 
−
    ! FFJ1
 
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    | subtask 1 & 2        [not able to run their code]  ||  style="text-align: center;" |  [PDF not provided] || [mailto:yangbih0914@gmail.com Yang-Bin Dell Fan], [mailto:lambert.fan@mirllab.org Zhe-Cheng Fan], [mailto:jang@csie.ntu.edu.tw Jyh-Shing Roger Jang]
 
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===Source-separated===
 
===Source-separated===
 
====Summary Results====
 
====Summary Results====
−
<csv>2018/ala/kugou/clean/summary_kugou_clean.csv</csv>
+
<csv>2019/ala/kugou/clean/summary_kugou_clean.csv</csv>
  
 
====Per-track results====
 
====Per-track results====
  
 
CW1
 
CW1
−
<csv>2018/ala/kugou/clean/CW1_kugou_clean.csv</csv>
+
<csv>2019/ala/kugou/clean/CW1_kugou_clean.csv</csv>
  
 
===Mix===
 
===Mix===
 
====Summary Results====
 
====Summary Results====
−
<csv>2018/ala/kugou/mix/summary_kugou_mix.csv</csv>
+
<csv>2019/ala/kugou/mix/summary_kugou_mix.csv</csv>
  
 
====Per-track results====
 
====Per-track results====
  
 
CW1
 
CW1
−
<csv>2018/ala/kugou/mix/CW1_kugou_mix.csv</csv>
+
<csv>2019/ala/kugou/mix/CW1_kugou_mix.csv</csv>
  
 
==Subtask2: English pop songs==
 
==Subtask2: English pop songs==
 
===Hansen's dataset a cappella===
 
===Hansen's dataset a cappella===
 
====Summary Results====
 
====Summary Results====
−
<csv>2018/ala/hansen/clean/summary_hansen_clean.csv</csv>
+
<csv>2019/ala/hansen/clean/summary_hansen_clean.csv</csv>
  
 
====Per-track results====
 
====Per-track results====
  
 
CW2
 
CW2
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<csv>2018/ala/hansen/clean/CW2_hansen_clean.csv</csv>
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<csv>2019/ala/hansen/clean/CW2_hansen_clean.csv</csv>
  
 
CW3
 
CW3
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<csv>2018/ala/hansen/clean/CW3_hansen_clean.csv</csv>
+
<csv>2019/ala/hansen/clean/CW3_hansen_clean.csv</csv>
  
 
GSLW1
 
GSLW1
−
<csv>2018/ala/hansen/clean/GSLW1_hansen_clean.csv</csv>
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<csv>2019/ala/hansen/clean/GSLW1_hansen_clean.csv</csv>
  
 
GSLW2
 
GSLW2
−
<csv>2018/ala/hansen/clean/GSLW2_hansen_clean.csv</csv>
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<csv>2019/ala/hansen/clean/GSLW2_hansen_clean.csv</csv>
  
 
GSLW3
 
GSLW3
−
<csv>2018/ala/hansen/clean/GSLW3_hansen_clean.csv</csv>
+
<csv>2019/ala/hansen/clean/GSLW3_hansen_clean.csv</csv>
  
  
 
===Hansen's dataset mix===
 
===Hansen's dataset mix===
 
====Summary Results====
 
====Summary Results====
−
<csv>2018/ala/hansen/mix/summary_hansen_mix.csv</csv>
+
<csv>2019/ala/hansen/mix/summary_hansen_mix.csv</csv>
  
 
====Per-track results====
 
====Per-track results====
  
 
CW2
 
CW2
−
<csv>2018/ala/hansen/mix/CW2_hansen_mix.csv</csv>
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<csv>2019/ala/hansen/mix/CW2_hansen_mix.csv</csv>
  
 
CW3
 
CW3
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<csv>2018/ala/hansen/mix/CW3_hansen_mix.csv</csv>
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<csv>2019/ala/hansen/mix/CW3_hansen_mix.csv</csv>
  
 
GSLW1
 
GSLW1
−
<csv>2018/ala/hansen/mix/GSLW1_hansen_mix.csv</csv>
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<csv>2019/ala/hansen/mix/GSLW1_hansen_mix.csv</csv>
  
 
GSLW2
 
GSLW2
−
<csv>2018/ala/hansen/mix/GSLW2_hansen_mix.csv</csv>
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<csv>2019/ala/hansen/mix/GSLW2_hansen_mix.csv</csv>
  
 
GSLW3
 
GSLW3
−
<csv>2018/ala/hansen/mix/GSLW3_hansen_mix.csv</csv>
+
<csv>2019/ala/hansen/mix/GSLW3_hansen_mix.csv</csv>
  
 
===Mauch's dataset===
 
===Mauch's dataset===
  
 
====Summary Results====
 
====Summary Results====
−
<csv>2018/ala/mauch/summary_mauch.csv</csv>
+
<csv>2019/ala/mauch/summary_mauch.csv</csv>
  
 
====Per-track results====
 
====Per-track results====
  
 
CW2
 
CW2
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<csv>2018/ala/mauch/CW2_mauch.csv</csv>
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<csv>2019/ala/mauch/CW2_mauch.csv</csv>
  
 
CW3
 
CW3
−
<csv>2018/ala/mauch/CW3_mauch.csv</csv>
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<csv>2019/ala/mauch/CW3_mauch.csv</csv>
  
 
GSLW1
 
GSLW1
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<csv>2018/ala/mauch/GSLW1_mauch.csv</csv>
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<csv>2019/ala/mauch/GSLW1_mauch.csv</csv>
  
 
GSLW2
 
GSLW2
−
<csv>2018/ala/mauch/GSLW2_mauch.csv</csv>
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<csv>2019/ala/mauch/GSLW2_mauch.csv</csv>
  
 
GSLW3
 
GSLW3
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====Summary Results====
 
====Summary Results====
  
−
<csv>2018/ala/gracenote/summary_gracenote.csv</csv>
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<csv>2019/ala/gracenote/summary_gracenote.csv</csv>
  
 
====Per-track results====
 
====Per-track results====
  
 
CW2
 
CW2
−
<csv>2018/ala/gracenote/CW2_gracenote.csv</csv>
+
<csv>2019/ala/gracenote/CW2_gracenote.csv</csv>
  
 
CW3
 
CW3
−
<csv>2018/ala/gracenote/CW3_gracenote.csv</csv>
+
<csv>2019/ala/gracenote/CW3_gracenote.csv</csv>
  
 
GSLW1
 
GSLW1
−
<csv>2018/ala/gracenote/GSLW1_gracenote.csv</csv>
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<csv>2019/ala/gracenote/GSLW1_gracenote.csv</csv>
  
 
GSLW2
 
GSLW2
−
<csv>2018/ala/gracenote/GSLW2_gracenote.csv</csv>
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<csv>2019/ala/gracenote/GSLW2_gracenote.csv</csv>
  
 
GSLW3
 
GSLW3
−
<csv>2018/ala/gracenote/GSLW3_gracenote.csv</csv>
+
<csv>2019/ala/gracenote/GSLW3_gracenote.csv</csv>

Revision as of 13:14, 4 November 2019

General Legend

Sub code Submission name Abstract Contributors
ED1 Audio2Lyrics_emirdemirel PDF Emir Demirel
GYL1 NUS PDF Chitralekha Gupta, Haizhou Li, Emre Yilmaz
JH1 Force Alignment with Kaldi PDF Jyh-Shing Roger Jang, Huang Hsiang-Yu
LJ2 Force Alignment with Kaldi PDF Chuan You Lin, Jyh-Shing Roger Jang, Huang Hsiang-Yu

Results

Subtask1: A cappella Mandarin Chinese pop songs

Source-separated

Summary Results

file /nema-raid/www/mirex/results/2019/ala/kugou/clean/summary_kugou_clean.csv not found

Per-track results

CW1 file /nema-raid/www/mirex/results/2019/ala/kugou/clean/CW1_kugou_clean.csv not found

Mix

Summary Results

file /nema-raid/www/mirex/results/2019/ala/kugou/mix/summary_kugou_mix.csv not found

Per-track results

CW1 file /nema-raid/www/mirex/results/2019/ala/kugou/mix/CW1_kugou_mix.csv not found

Subtask2: English pop songs

Hansen's dataset a cappella

Summary Results

file /nema-raid/www/mirex/results/2019/ala/hansen/clean/summary_hansen_clean.csv not found

Per-track results

CW2 file /nema-raid/www/mirex/results/2019/ala/hansen/clean/CW2_hansen_clean.csv not found

CW3 file /nema-raid/www/mirex/results/2019/ala/hansen/clean/CW3_hansen_clean.csv not found

GSLW1 file /nema-raid/www/mirex/results/2019/ala/hansen/clean/GSLW1_hansen_clean.csv not found

GSLW2 file /nema-raid/www/mirex/results/2019/ala/hansen/clean/GSLW2_hansen_clean.csv not found

GSLW3 file /nema-raid/www/mirex/results/2019/ala/hansen/clean/GSLW3_hansen_clean.csv not found


Hansen's dataset mix

Summary Results

file /nema-raid/www/mirex/results/2019/ala/hansen/mix/summary_hansen_mix.csv not found

Per-track results

CW2 file /nema-raid/www/mirex/results/2019/ala/hansen/mix/CW2_hansen_mix.csv not found

CW3 file /nema-raid/www/mirex/results/2019/ala/hansen/mix/CW3_hansen_mix.csv not found

GSLW1 file /nema-raid/www/mirex/results/2019/ala/hansen/mix/GSLW1_hansen_mix.csv not found

GSLW2 file /nema-raid/www/mirex/results/2019/ala/hansen/mix/GSLW2_hansen_mix.csv not found

GSLW3 file /nema-raid/www/mirex/results/2019/ala/hansen/mix/GSLW3_hansen_mix.csv not found

Mauch's dataset

Summary Results

file /nema-raid/www/mirex/results/2019/ala/mauch/summary_mauch.csv not found

Per-track results

CW2 file /nema-raid/www/mirex/results/2019/ala/mauch/CW2_mauch.csv not found

CW3 file /nema-raid/www/mirex/results/2019/ala/mauch/CW3_mauch.csv not found

GSLW1 file /nema-raid/www/mirex/results/2019/ala/mauch/GSLW1_mauch.csv not found

GSLW2 file /nema-raid/www/mirex/results/2019/ala/mauch/GSLW2_mauch.csv not found

GSLW3

Track ASE PCS PCETW
Abba.KnowingMeKnowingYou 16.78 0.013470170808295 0
Bangles.EternalFlame 11.14 0.02898885485713 0.027450980392157
Blondie.CallMe 38.38 0 0
Duffy.WarwickAvenue 22.44 0.002410707267485 0.003787878787879
DuranDuran.OrdinaryWorld 26.87 0.026182638371089 0.030651340996169
FranzFerdinand-DoYouWanTo 13.38 0.00161317780798 0
Martika.ToySoldiers 21.94 0.0166667440527 0.03
Muse.GuidingLight 19.4 0.023893393487038 0.008620689655172
OtisRedding.TheDockOfTheBay 41.62 0 0
RM-P082 36.45 0.002038977644714 0
RM-P084 9.48 0.08661632622508 0.2
Queen.WeAreTheChampions 26.9 0 0
RobertPalmer.AddictedToLove 31.52 0 0
Santana.BlackMagicWoman 29.5 0.123035938934082 0
SimonAndGarfunkel.Cecilia 38.23 0 0
TakeThat.BackForGood 10.99 0.028435153463603 0.047619047619048
TinaTurner.WhatsLoveGotToDoWithIt 25.93 0.02372512809696 0.015479876160991
Toto.Africa 11.81 0.002388174061774 0.018939393939394
U2.WithOrWithoutYou 14.81 0.011272516767769 0.005235602094241
Zweieck.She 22.05 0.00600489576593 0.008583690987124

download these results as csv


Gracenote dataset

Summary Results

file /nema-raid/www/mirex/results/2019/ala/gracenote/summary_gracenote.csv not found

Per-track results

CW2 file /nema-raid/www/mirex/results/2019/ala/gracenote/CW2_gracenote.csv not found

CW3 file /nema-raid/www/mirex/results/2019/ala/gracenote/CW3_gracenote.csv not found

GSLW1 file /nema-raid/www/mirex/results/2019/ala/gracenote/GSLW1_gracenote.csv not found

GSLW2 file /nema-raid/www/mirex/results/2019/ala/gracenote/GSLW2_gracenote.csv not found

GSLW3 file /nema-raid/www/mirex/results/2019/ala/gracenote/GSLW3_gracenote.csv not found

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