Difference between revisions of "2025:Audio Chord Estimation Results"

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| [http://futuremirex.com/portal/wp-content/uploads/2025/audio-chord-estimation/MD1.pdf PDF]
 
| Masayuki Doai
 
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| wu-ensemble
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| [http://futuremirex.com/portal/wp-content/uploads/2025/audio-chord-estimation/wu-ensemble.pdf PDF]
 
| Yiwei Ding, Christof Weiß
 
| Yiwei Ding, Christof Weiß
 
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| wu-single
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| [http://futuremirex.com/portal/wp-content/uploads/2025/audio-chord-estimation/wu-single.pdf PDF]
 
| Yiwei Ding, Christof Weiß
 
| Yiwei Ding, Christof Weiß
 
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| Semi-Supervised Audio Chord Estimator Based on Disentangled Generative Modeling
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| [http://futuremirex.com/portal/wp-content/uploads/2025/audio-chord-estimation/YK1.pdf PDF]
 
| Yiming Wu, Kento Yoshida
 
| Yiming Wu, Kento Yoshida
 
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| A Mamba-Based Model for Automatic Chord Recognition
 
| A Mamba-Based Model for Automatic Chord Recognition
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| [http://futuremirex.com/portal/wp-content/uploads/2025/audio-chord-estimation/BMACE.pdf PDF]
 
| Chunyu Yuan, Jiyeoung Sim, Johanna Devaney
 
| Chunyu Yuan, Jiyeoung Sim, Johanna Devaney
 
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Latest revision as of 09:10, 19 September 2025

Submissions

Submission Title PDF Authors
Baseline: Chordino NNLS Chroma v1.1 Link
Baseline: ISMIR2019 Large-Vocabulary Chord Transcription via Chord Structure Decomposition Link
MD1 Degree-Based Automatic Chord Recognition with Enharmonic Distinction PDF Masayuki Doai
wu-ensemble wu-ensemble PDF Yiwei Ding, Christof Weiß
wu-single wu-single PDF Yiwei Ding, Christof Weiß
YK1 Semi-Supervised Audio Chord Estimator Based on Disentangled Generative Modeling PDF Yiming Wu, Kento Yoshida
BMACE A Mamba-Based Model for Automatic Chord Recognition PDF Chunyu Yuan, Jiyeoung Sim, Johanna Devaney

Test Sets

Main Test Sets

The following datasets are served as pure test sets. No system is allowed to train on them.

  • Billboard 2013: The held-out portion of the McGill Billboard dataset, containing mainly western pop songs from the Billboard chart.
  • Yamaha_JPOP: A private dataset annotated by Yamaha Corporation. The dataset contains 200 JPOP songs.
  • Yamaha_Balanced: A private dataset annotated by Yamaha Corporation. The dataset contains 241 songs. While it is still biased towards JPOP songs, the dataset covers a wider range of genres: J.Pop (10.37%), Rock (10.37%), J.Enka (10.37%), J.Kayoukyoku (10.37%), Soundtrack (10.37%), Western Pop (10.37%), Children's Song (10.37%), R&B (6.22%), Hiphop (4.56%), Jazz (2.49%), Dance (2.49%), World (2.07%), Techno (1.24%), Easy listening (1.24%), J.Minyou (1.24%), Others (5.81%).

Additional Test Sets

These are datasets that may not be strictly held-out test sets. Some models might have been trained on these datasets; for specific details, please refer to the extended abstracts of each model.

  • Billboard 2012: The public portion of the McGill Billboard dataset.
  • RWC Popular: 100 pop songs from the RWC (Real World Computing) Music Database. 20% songs with English lyrics and 80% songs with Japanese lyrics.

Main Results

The following datasets are served as pure test sets. No system is allowed to train on them.

Billboard2013

Group MirexRoot MirexMajMin MirexMajMinBass MirexSevenths MirexSeventhsBass MeanSeg UnderSeg OverSeg
BMACE 55.72 8.88 8.70 2.52 2.45 68.16 90.86 56.60
MD1 81.35 79.15 77.91 66.40 65.33 86.17 85.50 88.89
YK1 81.01 78.10 75.41 64.53 62.05 85.50 85.08 87.49
wu-ensemble 74.64 71.97 70.72 55.06 53.96 83.19 86.29 82.20
wu-single 75.77 73.14 71.74 55.41 54.15 83.16 85.44 83.08
Baseline: Chordino 71.06 67.18 65.09 48.88 47.06 81.60 83.14 82.71
Baseline: ISMIR2019 78.61 76.39 74.72 64.15 62.65 83.39 78.57 92.78

YAMAHA_Balanced

Group MirexRoot MirexMajMin MirexMajMinBass MirexSevenths MirexSeventhsBass MeanSeg UnderSeg OverSeg
BMACE 58.92 12.59 12.29 4.52 4.34 71.62 91.05 60.47
MD1 81.83 80.22 78.87 64.13 63.14 88.09 88.67 88.47
YK1 82.53 79.71 75.60 66.02 62.31 88.94 89.78 89.33
wu-ensemble 82.54 81.29 78.99 62.84 60.84 87.48 88.68 87.43
wu-single 81.37 79.69 77.61 61.60 59.84 87.03 89.81 85.89
Baseline: Chordino 77.57 74.64 71.59 56.38 53.90 86.51 87.25 87.48
Baseline: ISMIR2019 82.00 81.16 79.69 66.97 65.77 89.04 86.43 93.49

YAMAHA_JPop

Group MirexRoot MirexMajMin MirexMajMinBass MirexSevenths MirexSeventhsBass MeanSeg UnderSeg OverSeg
BMACE 52.38 11.90 11.65 2.37 2.23 71.98 90.23 60.42
MD1 79.34 77.10 76.07 55.59 54.71 88.00 88.13 88.20
YK1 80.13 77.03 72.85 61.24 57.26 89.42 89.71 89.49
wu-ensemble 79.58 77.58 75.57 54.36 52.58 87.22 88.44 86.55
wu-single 78.87 76.56 74.66 55.35 53.60 87.19 89.30 85.70
Baseline: Chordino 74.49 71.99 69.24 52.40 49.97 86.66 85.89 88.28
Baseline: ISMIR2019 81.49 79.99 78.58 62.81 61.61 90.09 87.21 93.88

Additional Results

Below are results on datasets that may not be strictly held-out test sets. Some models might have been trained on these datasets; for specific details, please refer to the extended abstracts of each model.

Billboard2012

Group MirexRoot MirexMajMin MirexMajMinBass MirexSevenths MirexSeventhsBass MeanSeg UnderSeg OverSeg
BMACE 58.45 9.13 9.00 2.91 2.86 69.55 92.02 57.41
MD1 85.11 83.98 82.76 74.12 73.12 88.80 88.63 89.78
YK1 85.90 84.66 81.81 77.22 74.45 88.43 87.88 89.58
wu-ensemble 78.26 77.15 75.58 59.99 58.79 84.42 87.98 82.57
wu-single 79.23 78.21 76.76 60.23 59.07 84.87 87.19 84.24
Baseline: Chordino 74.04 72.11 70.05 55.24 53.28 83.69 85.33 83.48

RWC-Popular

Group MirexRoot MirexMajMin MirexMajMinBass MirexSevenths MirexSeventhsBass MeanSeg UnderSeg OverSeg
BMACE 56.48 11.97 11.78 2.41 2.30 72.59 90.92 61.06
MD1 83.98 81.18 79.42 66.53 64.83 88.53 88.53 88.84
YK1 88.76 87.27 81.14 76.88 70.90 91.90 91.55 92.43
wu-ensemble 81.87 80.30 77.58 62.65 60.25 87.51 89.95 85.65
wu-single 82.48 81.35 78.48 62.86 60.28 87.81 89.47 86.64
Baseline: Chordino 78.97 77.78 74.13 63.15 59.72 88.64 88.07 89.76


Task Captain's Note