Clustering music recordings by their keys

ISMIR 2008 - 9th International Conference on Music Information Retrieval

Volumn , Issue , 2008, Pages 319-324

  Liu, Yuxiang ^a,b   Wang, Ye ^b   Shenoy, Arun ^d   Tsai, Wei Ho ^c   Cai, Lianhong ^a  

^a TSINGHUA UNIVERSITY   (China)

^b NATIONAL UNIVERSITY OF SINGAPORE   (Singapore)

^c NATIONAL TAIPEI UNIVERSITY OF TECHNOLOGY   (Taiwan)

^d NONE

Author keywords

[No Author keywords available]

Indexed keywords

ACOUSTIC SIGNALS; CROSS CORRELATIONS; DATA SETS; DISTANCE METRICS; EFFECTIVE TOOL; EMPIRICAL EVALUATIONS; HIGH-LEVEL FEATURES; IDENTIFICATION TECHNIQUES; KEY ASSIGNMENT; MUSIC RECORDING; MUSICAL AUDIO; MUSICAL FEATURES; NUMBER OF CLUSTERS; RAND INDEX; UNSUPERVISED APPROACHES; UNSUPERVISED CLUSTERING;

AUDIO ACOUSTICS; INFORMATION RETRIEVAL;

AUDIO RECORDINGS;

EID: 73249150711     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (23)

1. Chai, W. and Vercoe, B., Detection of key change in classical piano music, Proc. of the International Symposium on Music Information Retrieval, 2005
2. Chew, E., The spiral array: an algorithm for determining key boundaries, Music and Artificial Intelligence, Vol. 2445, 2002
3. Chuan, C. H. and Chew, E., Fuzzy Analysis in pitch-class determination for polyphonic audio key finding, Proc. of the International Symposium on Music Information Retrieval, 2005
4. Gómez, E. and Herrera, P., Estimating the tonality of polyphonic audio files cognitive versus machine learning modelling strategies, Proc. of the International Symposium on Music Information Retrieval, 2004
5. Hubert, L. and Arabie, P., Comparing partitions, Journal of Classification, Vol. 2, Issue 1, 1985
6. izmirli, O., Tonal similarity from audio using a template based attractor model, Proc. of the International Symposium on Music Information Retrieval, 2005
7. Kaufman, L. and Rousseuw, P. J., Finding Groups in Data: An Introduction to Cluster Analysis, John Wiley and Sons, New York, 1990
8. Klabbers, E. and Veldhuis, R., Reducing audible spectral discontinuities, IEEE Trans. on Speech and Audio Processing, Vol. 9, Issue 1, 2001.
9. Krumhansl, C., Cognitive Foundations of Musical Pitch, Oxford University Press, New York, 1990
10. Kullback, S. and Leibler, R. A., On information and sufficiency, Annals of Mathematical Statistics Vol. 22, Issue 1, 1951
11. Lee, K., Slaney M., Acoustic chord transcription and key extraction from audio using key-dependent HMMs trained on synthesized audio, IEEE Trans. on Audio, Speech, and Language Processing, Vol. 16, No. 2, 2008
12. Martens, G., De Meyer, H., etc. Tree-based versus distance-based key recognition in musical audio, Soft Computing - a Fusion of Foundations, Methodologies and Applications archive, Vol. 9, Issue 8, 2005
13. Pauws, S., Extracting the key from music, Intelligent Algorithms in Ambient and Biomedical Computing, Springer, Netherlands, 2006
14. Peeters, G., Musical key estimation of audio signal based on HMM modeling of chroma vectors, Proc. of DAFX, McGill, Montreal, Canada, 2006.
15. Rand, W. M., Objective criteria for the evaluation of clustering methods, Journal of the American Statistical Association, Vol. 66, No. 336, 1971.
16. Shenoy, A. and Wang, Y., Key, chord, and rhythm tracking of popular music recordings", Computer Music Journal, Vol. 29, No. 3, 2005
17. Shepard, R., "Circularity in judgments of relative pitch,", The Journal of the Acoustical Society of America, Vol. 36, Issue 12, 1964
18. Solomonoff, A., Mielke, A., etc. Clustering speakers by their voices, Proc. of the IEEE International Conf. on Acoustics, Speech, and Signal Processing, 1998.
19. Temperley, D., A Bayesian approach to key-finding, Proc. of the Second International Conf. on Music and Artificial Intelligence, 2002
20. Tsai, W. H., Rodgers, D. and Wang, H. M., Blind clustering of popular music recordings based on singer voice characteristics, Computer Music Journal, Vol. 28, No. 3: 2004
21. Tsai, W. H., Wang, H. M., Speaker Clustering Based on Minimum Rand Index, Proc. of the IEEE International Conf. on Acoustics, Speech, and Signal Processing, 2007
22. Veldhuis, R. and Klabbers, E., On the computation of the Kullback-Leibler measure for spectral distances, IEEE Trans. on Speech and Audio Processing, Vol. 11, No. 1, 2003.
23. Zhu, Y. W. and Kankanhalli, M. S., Precise pitch profile feature extraction from musical audio for key detection, IEEE Trans. on Multimedia, Vol. 8, No. 3, 2006.