Automatic chord recognition from audio using a supervised HMM trained with audio-from-symbolic data

Proceedings of the ACM International Multimedia Conference and Exhibition

Volumn , Issue , 2006, Pages 11-20

  Lee, Kyogu ^a   Slaney, Malcolm ^b  

^a STANFORD UNIVERSITY   (United States)

^b YAHOO RESEARCH   (United States)

Author keywords

Chord recognition; Hidden Markov model; MIDI; Supervised learning

Indexed keywords

CHORD RECOGNITION; HIDDEN MARKOV MODEL; MIDI;

AUDIO ACOUSTICS; DATA ACQUISITION; HARMONIC ANALYSIS; HIDDEN MARKOV MODELS; PARAMETER ESTIMATION; SUPERVISED LEARNING;

SPEECH RECOGNITION;

EID: 34547481982     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1178723.1178726     Document Type: Conference Paper

References (12)

1. J. P. Bello and J. Pickens. A robust mid-level representation for harmonic content in music signals. In Proceedings of the International Symposium on Music Information Retrieval, London, UK, 2005.
2. J. C. Brown. Calculation of a constant-Q spectral transform. Journal of the Acoustical Society of America, 89(1):425-434, 1990.
3. T. Fujishima,. Realtime chord recognition of musical sound: A system using Common Lisp Music. In Proceedings of the International Computer Music Conference, Beijing, 1999. International Computer Music Association.
4. E. Gomez and P. Herrera. Automatic extraction of tonal metadata from polyphonic audio recordings. In Proceedings of the Audio Engineering Society, London, 2004. Audio Engineering Society.
5. C. A. Harte and M. B. Sandler. Automatic chord identification using a quantised chromagram. In Proceedings of the Audio Engineering Society, Spain, 2005. Audio Engineering Society.
6. S. Kostka and D. Payne. Tonal harmony with an introduction to 20th-century music. McGraw-Hill, 2004.
7. C. L. Krumhansl. Cognitive Foundations of Musical Pitch. Oxford University Press, 1990.
8. K. Lee and M. Slaney. Automatic chord recognition from audio using an HMM with supervised learning (accpeted for publication). In Proceedings of the International Symposium on Music Information Retrieval, 2006.
9. S. Pauws. Musical key extraction from audio. In Proceedings of the International Symposium on Music Information Retrieval, Barcelona, Spain, 2004.
10. L. R. Rabiner. A tutorial on hidden Markov models and selected applications in speech recognition. Proceedings of the IEEE, 77(2):257-286, 1989.
11. A. Sheh and D. P. Ellis. Chord segmentation and recognition using EM-trained hidden Markov models. In Proceedings of the International Symposium on Music Information Retrieval, Baltimore, MD, 2003.
12. D. Temperley. The cognition of basic musical structures. The MIT Press, 2001.