Difference between revisions of "2009:Audio Music Mood Classification Results"
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'''SS''' = [https://music-ir.org/mirex/2009/results/abs/SS.pdf Klaus Seyerlehner, Markus Schedl]<br /> | '''SS''' = [https://music-ir.org/mirex/2009/results/abs/SS.pdf Klaus Seyerlehner, Markus Schedl]<br /> | ||
'''TAOS'''= [https://music-ir.org/mirex/2009/results/abs/TAOS.pdf Emiru Tsunoo, Taichi Akase, Nobutaka Ono, Shigeki Sagayama]<br /> | '''TAOS'''= [https://music-ir.org/mirex/2009/results/abs/TAOS.pdf Emiru Tsunoo, Taichi Akase, Nobutaka Ono, Shigeki Sagayama]<br /> | ||
| − | '''MTG1''' = [https://music-ir.org/mirex/2009/results/abs/MTG_train.pdf | + | '''MTG1''' = [https://music-ir.org/mirex/2009/results/abs/MTG_train.pdf Nicolas Wack, Enric Guaus, Cyril Laurier, Owen Meyers, Ricard Marxer, Dmitry Bogdanov, Joan Serr├á, Perfecto Herrera (false, rca)]<br /> |
| − | '''MTG2''' = [https://music-ir.org/mirex/2009/results/abs/MTG_train.pdf | + | '''MTG2''' = [https://music-ir.org/mirex/2009/results/abs/MTG_train.pdf Nicolas Wack, Enric Guaus, Cyril Laurier, Owen Meyers, Ricard Marxer, Dmitry Bogdanov, Joan Serr├á, Perfecto Herrera (true, rca)]<br /> |
| − | '''MTG3''' = [https://music-ir.org/mirex/2009/results/abs/MTG_train.pdf | + | '''MTG3''' = [https://music-ir.org/mirex/2009/results/abs/MTG_train.pdf Nicolas Wack, Enric Guaus, Cyril Laurier, Owen Meyers, Ricard Marxer, Dmitry Bogdanov, Joan Serr├á, Perfecto Herrera (false, simca)]<br /> |
| − | '''MTG4''' = [https://music-ir.org/mirex/2009/results/abs/MTG_train.pdf | + | '''MTG4''' = [https://music-ir.org/mirex/2009/results/abs/MTG_train.pdf Nicolas Wack, Enric Guaus, Cyril Laurier, Owen Meyers, Ricard Marxer, Dmitry Bogdanov, Joan Serr├á, Perfecto Herrera (true, simca)]<br /> |
| − | '''MTG5''' = [https://music-ir.org/mirex/2009/results/abs/MTG_train.pdf | + | '''MTG5''' = [https://music-ir.org/mirex/2009/results/abs/MTG_train.pdf Nicolas Wack, Enric Guaus, Cyril Laurier, Owen Meyers, Ricard Marxer, Dmitry Bogdanov, Joan Serr├á, Perfecto Herrera (false, svm)]<br /> |
| − | '''MTG6''' = [https://music-ir.org/mirex/2009/results/abs/MTG_train.pdf | + | '''MTG6''' = [https://music-ir.org/mirex/2009/results/abs/MTG_train.pdf Nicolas Wack, Enric Guaus, Cyril Laurier, Owen Meyers, Ricard Marxer, Dmitry Bogdanov, Joan Serr├á, Perfecto Herrera (true, svm)]<br /> |
'''XLZZG''' = [https://music-ir.org/mirex/2009/results/abs/XLZZG.pdf Jieping Xu, Yi Liu, Tao Zheng, Chao Zhen, Yue Gao (RUC_1)]<br /> | '''XLZZG''' = [https://music-ir.org/mirex/2009/results/abs/XLZZG.pdf Jieping Xu, Yi Liu, Tao Zheng, Chao Zhen, Yue Gao (RUC_1)]<br /> | ||
'''XZZ''' = [https://music-ir.org/mirex/2009/results/abs/XZZ.pdf JiePing Xu, Chao Zhen, Tao Zheng (RUC_2)]<br /> | '''XZZ''' = [https://music-ir.org/mirex/2009/results/abs/XZZ.pdf JiePing Xu, Chao Zhen, Tao Zheng (RUC_2)]<br /> | ||
Revision as of 12:00, 23 October 2009
Contents
Introduction
These are the results for the 2009 running of the Audio Music Mood Classification task. For background information about this task set please refer to the Audio Music Mood Classification page. The data was created by Xiao Hu and consists of 600 files organized into 5 mood "clusters".
Mood Clusters
The 5 mood clusters were derived from the AMG mood repository.
* Cluster_1: passionate, rousing, confident,boisterous, rowdy * Cluster_2: rollicking, cheerful, fun, sweet, amiable/good natured * Cluster_3: literate, poignant, wistful, bittersweet, autumnal, brooding * Cluster_4: humorous, silly, campy, quirky, whimsical, witty, wry * Cluster_5: aggressive, fiery,tense/anxious, intense, volatile,visceral
For more information on the clusters, please see
Hu, Xiao and J. Stephen Downie (2007) Exploring mood metadata: Relationships with genre, artist and usage metadata, In the 8th International Conference on Music Information Retrieval (ISMIR 2007), Vienna, September 23-27, 2007.
Data
There are 600 audio clips with 120 in each mood cluster. Each clip belongs to only one mood cluster. The clips were chosen from the APM audio set .
The mood cluster labels of the clips were firstly suggested by their metadata provided by APM and then decided by human validations using the Evalutron6000
Each mood cluster covers a variety of genres: each category covers about 7 major genres (with 20-30 tracks each) and a few minor genres, and the distribution among major genres within each category is made as even as possible.
Audio format: 30 second clips, 22.05kHz, mono, 16bit, WAV files; The data were evenly split into 3 folds.
For more information on the dataset and evaluation methods, please see
X. Hu, J. S. Downie, C. Laurier, M. Bay, A.Ehmann (2008) The 2007 MIREX Audio Mood Classification Task: Lessons Learned, In the 9th International Symposium on Music Information Retrieval (ISMIR 2008), Philadelphia, Sept. 2008
General Legend
Team ID
ANO= Anonymous
BP1= Juan José Burred, Geoffroy Peeters (file)
BP2 = Juan José Burred, Geoffroy Peeters (tw)
CL1 = Chuan Cao, Ming Li
CL2 = Chuan Cao, Ming Li
FCY1 = Tao Feng, XiaoOu Chen, DeShun Yang
FCY2 = Tao Feng, XiaoOu Chen, DeShun Yang
GP = Geoffroy Peeters
GT1 = George Tzanetakis (mono)
GT2 = George Tzanetakis (stereo)
GLR1 = A. Grecu, T. Lidy, A. Rauber (full)
GLR2 = A. Grecu, T. Lidy, A. Rauber (template)
HNOS1 = Takashi Hasegawa, Takuya Nishimoto, Nobutaka Ono, Shigeki Sagayama (tcca)
HNOS2 = Takashi Hasegawa, Takuya Nishimoto, Nobutaka Ono, Shigeki Sagayama (tcck)
HNOS3 = Takashi Hasegawa, Takuya Nishimoto, Nobutaka Ono, Shigeki Sagayama (tccl)
HNOS4 = Takashi Hasegawa, Takuya Nishimoto, Nobutaka Ono, Shigeki Sagayama (tcpk)
HW1 = Huaxin Wang
HW2 = Huaxin Wang
VA1 = T. Lidy, A. Grecu, A. Rauber, A. Pertusa, P. J. Ponce de Léon, J. M. Iñesta (WMV)
VA2 = T. Lidy, A. Grecu, A. Rauber, A. Pertusa, P. J. Ponce de Léon, J. M. Iñesta (BWWV)
LZG = Yi Liu, Tao Zheng, Yue Gao (RUC_1)
RK1 = Preeti Rao, Sujeet Kini
RK2 = Preeti Rao, Sujeet Kini
SS = Klaus Seyerlehner, Markus Schedl
TAOS= Emiru Tsunoo, Taichi Akase, Nobutaka Ono, Shigeki Sagayama
MTG1 = Nicolas Wack, Enric Guaus, Cyril Laurier, Owen Meyers, Ricard Marxer, Dmitry Bogdanov, Joan Serrà, Perfecto Herrera (false, rca)
MTG2 = Nicolas Wack, Enric Guaus, Cyril Laurier, Owen Meyers, Ricard Marxer, Dmitry Bogdanov, Joan Serrà, Perfecto Herrera (true, rca)
MTG3 = Nicolas Wack, Enric Guaus, Cyril Laurier, Owen Meyers, Ricard Marxer, Dmitry Bogdanov, Joan Serrà, Perfecto Herrera (false, simca)
MTG4 = Nicolas Wack, Enric Guaus, Cyril Laurier, Owen Meyers, Ricard Marxer, Dmitry Bogdanov, Joan Serrà, Perfecto Herrera (true, simca)
MTG5 = Nicolas Wack, Enric Guaus, Cyril Laurier, Owen Meyers, Ricard Marxer, Dmitry Bogdanov, Joan Serrà, Perfecto Herrera (false, svm)
MTG6 = Nicolas Wack, Enric Guaus, Cyril Laurier, Owen Meyers, Ricard Marxer, Dmitry Bogdanov, Joan Serrà, Perfecto Herrera (true, svm)
XLZZG = Jieping Xu, Yi Liu, Tao Zheng, Chao Zhen, Yue Gao (RUC_1)
XZZ = JiePing Xu, Chao Zhen, Tao Zheng (RUC_2)
Overall Summary Results
Raw Classification Accuracy Averaged Over Three Train/Test Folds
file /nema-raid/www/mirex/results/audiomood/summary_audiomood.csv not found
Accuracy Across Folds
file /nema-raid/www/mirex/results/audiomood/audiomood_Accuracy.csv not found
Accuracy Across Categories
file /nema-raid/www/mirex/results/audiomood/audiomood_Accuracy_Per_Class.csv not found
Friedman's Tests for Significant Differences
Classes vs. System Tukey-Kramer HSD Multi-Comparisons
The Friedman test was run in MATLAB against the average accuracy for each class. The Tukey-Kramer HSD multi-comparison data below was generated using the following MATLAB instruction. Command:
[c, m, h, gnames] = multicompare(stats, 'ctype', 'tukey-kramer', 'estimate', 'friedman', 'alpha', 0.05);
file /nema-raid/www/mirex/results/audiomood/audiomood_Accuracy_Per_Class.friedman.tukeyKramerHSD.csv not found
Folds vs. Systems Tukey-Kramer HSD Multi-Comparison
The Friedman test was run in MATLAB against the accuracy for each fold. The Tukey-Kramer HSD multi-comparison data below was generated using the following MATLAB instruction. Command:
[c, m, h, gnames] = multicompare(stats, 'ctype', 'tukey-kramer', 'estimate', 'friedman', 'alpha', 0.05);
file /nema-raid/www/mirex/results/audiomood/audiomood_Accuracy.friedman.tukeyKramerHSD.csv not found
Results By Algorithm
(.tgz)
ANO= Anonymous
BP1= Juan José Burred, Geoffroy Peeters (file)
BP2 = Juan José Burred, Geoffroy Peeters (tw)
CL1 = Chuan Cao, Ming Li
CL2 = Chuan Cao, Ming Li
FCY1 = Tao Feng, XiaoOu Chen, DeShun Yang
FCY2 = Tao Feng, XiaoOu Chen, DeShun Yang
GP = Geoffroy Peeters
GT1 = George Tzanetakis (mono)
GT2 = George Tzanetakis (stereo)
GLR1 = A. Grecu, T. Lidy, A. Rauber (full)
GLR2 = A. Grecu, T. Lidy, A. Rauber (template)
HNOS1 = Takashi Hasegawa, Takuya Nishimoto, Nobutaka Ono, Shigeki Sagayama (tcca)
HNOS2 = Takashi Hasegawa, Takuya Nishimoto, Nobutaka Ono, Shigeki Sagayama (tcck)
HNOS3 = Takashi Hasegawa, Takuya Nishimoto, Nobutaka Ono, Shigeki Sagayama (tccl)
HNOS4 = Takashi Hasegawa, Takuya Nishimoto, Nobutaka Ono, Shigeki Sagayama (tcpk)
HW1 = Huaxin Wang
HW2 = Huaxin Wang
VA1 = T. Lidy, A. Grecu, A. Rauber, A. Pertusa, P. J. Ponce de Léon, J. M. Iñesta (WMV)
VA2 = T. Lidy, A. Grecu, A. Rauber, A. Pertusa, P. J. Ponce de Léon, J. M. Iñesta (BWWV)
LZG = Yi Liu, Tao Zheng, Yue Gao (RUC_1)
RK1 = Preeti Rao, Sujeet Kini
RK2 = Preeti Rao, Sujeet Kini
SS = Klaus Seyerlehner, Markus Schedl
TAOS= Emiru Tsunoo, Taichi Akase, Nobutaka Ono, Shigeki Sagayama
MTG1 = N. Wack, E. Guaus, C. Laurier, O. Meyers, R. Marxer, D. Bogdanov, J. Serrà, P. Herrera (false, rca)
MTG2 = N. Wack, E. Guaus, C. Laurier, O. Meyers, R. Marxer, D. Bogdanov, J. Serrà, P. Herrera (true, rca)
MTG3 = N. Wack, E. Guaus, C. Laurier, O. Meyers, R. Marxer, D. Bogdanov, J. Serrà, P. Herrera (false, simca)
MTG4 = N. Wack, E. Guaus, C. Laurier, O. Meyers, R. Marxer, D. Bogdanov, J. Serrà, P. Herrera (true, simca)
MTG5 = N. Wack, E. Guaus, C. Laurier, O. Meyers, R. Marxer, D. Bogdanov, J. Serrà, P. Herrera (false, svm)
MTG6 = N. Wack, E. Guaus, C. Laurier, O. Meyers, R. Marxer, D. Bogdanov, J. Serrà, P. Herrera (true, svm)
XLZZG = Jieping Xu, Yi Liu, Tao Zheng, Chao Zhen, Yue Gao (RUC_1)
XZZ = JiePing Xu, Chao Zhen, Tao Zheng (RUC_2)
Run Times
file /nema-raid/www/mirex/results/mood.runtime.csv not found TBA
