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ICASSP
2011
IEEE

Polyphonic audio-to-score alignment based on Bayesian Latent Harmonic Allocation Hidden Markov Model

8 years 3 months ago
Polyphonic audio-to-score alignment based on Bayesian Latent Harmonic Allocation Hidden Markov Model
This paper presents a Bayesian method for temporally aligning a music score and an audio rendition. A critical problem in audio-toscore alignment is in dealing with the wide variety of timbre and volume of the audio rendition. In contrast with existing works that achieve this through ad-hoc feature design or careful training of tone models, we propose a Bayesian audio-to-score alignment method by modeling music performance as a Bayesian Hidden Markov Model, each state of which emits a Bayesian signal model based on Latent Harmonic Allocation. After attenuating reverberation, variational Bayes method is used to iteratively adapt the alignment, instrument tone model and the volume balance at each position of the score. The method is evaluated using sixty works of classical music of a variety of instrumentation ranging from solo piano to full orchestra. We verify that our method improves the alignment accuracy compared to dynamic time warping based on chroma vector for orchestral music, ...
Akira Maezawa, Hiroshi G. Okuno, Tetsuya Ogata, Ma
Added 21 Aug 2011
Updated 21 Aug 2011
Type Journal
Year 2011
Where ICASSP
Authors Akira Maezawa, Hiroshi G. Okuno, Tetsuya Ogata, Masataka Goto
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