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Multidimensional humming transcription using a statistical approach for query by humming systems

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3 Author(s)
Hsuan-Huei Shih ; Dept. of Electr. Eng., Univ. of Southern California, Los Angeles, CA, USA ; Narayanan, S.S. ; Kuo, C.-C.J.

A new statistical pattern recognition approach applied to human humming transcription is proposed. A musical note has two important attributes, i.e. pitch and duration. The proposed algorithm generates multidimensional humming transcriptions, which contain both pitch and duration information. Query by humming provides a natural means for content-based retrieval from music databases, and this research provides a robust frontend for such an application. The segment of a note in the humming waveform is modeled by a hidden Markov model (HMM), while the pitch of the note is modeled by a pitch model using a Gaussian mixture model. Preliminary real-time recognition experiments are carried out with models trained by data obtained from eight human subjects, and an overall correct recognition rate of around 80% is demonstrated.

Published in:

Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03). 2003 IEEE International Conference on  (Volume:5 )

Date of Conference:

6-10 April 2003