An HMM-based pitch tracker for audio queries

In this paper we present an approach to the transcription of musical queries based on a HMM. The HMM is used to model the audio features related to the singing voice, and the transcription is obtained through Viterbi decoding. We report our preliminary work on evaluation of the system.

[1]  Christopher Raphael,et al.  Automatic Segmentation of Acoustic Musical Signals Using Hidden Markov Models , 1999, IEEE Trans. Pattern Anal. Mach. Intell..

[2]  Marc Leman,et al.  An Auditory Model Based Transcriber of Singing Sequences , 2002, ISMIR.

[3]  Hideki Kawahara,et al.  YIN, a fundamental frequency estimator for speech and music. , 2002, The Journal of the Acoustical Society of America.

[4]  Biing-Hwang Juang,et al.  Fundamentals of speech recognition , 1993, Prentice Hall signal processing series.

[5]  Guy J. Brown,et al.  Pitch tracking based on statistical anticipation , 2001, IJCNN'01. International Joint Conference on Neural Networks. Proceedings (Cat. No.01CH37222).

[6]  Nicola Orio,et al.  Musical information retrieval using melodic surface , 1999, DL '99.