NDLI: Bayesian nonparametric music parser

Content Provider	IEEE Xplore Digital Library
Author	Nakano, M. Ohishi, Y. Kameoka, H. Mukai, R. Kashino, K.
Copyright Year	2012
Description	Author affiliation: NTT Communication Science Laboratories, NTT Corporation, 3-1 Morinosato Wakamiya, Atsugi, Kanagawa 243-0198, Japan (Nakano, M.; Ohishi, Y.; Kameoka, H.; Mukai, R.; Kashino, K.)
Abstract	This paper proposes a novel representation of music that can be used for similarity-based music information retrieval, and also presents a method that converts an input polyphonic audio signal to the proposed representation. The representation involves a 2-dimensional tree structure, where each node encodes the musical note and the dimensions correspond to the time and simultaneous multiple notes, respectively. Since the temporal structure and the synchrony of simultaneous events are both essential in music, our representation reflects them explicitly. In the conventional approaches to music representation from audio, note extraction is usually performed prior to structure analysis, but accurate note extraction has been a difficult task. In the proposed method, note extraction and structure estimation is performed simultaneously and thus the optimal solution is obtained with a unified inference procedure. That is, we propose an extended 2-dimensional infinite probabilistic context-free grammar and a sparse factor model for spectrogram analysis. An efficient inference algorithm, based on Markov chain Monte Carlo sampling and dynamic programming, is presented. The experimental results show the effectiveness of the proposed approach.
Starting Page	461
Ending Page	464
File Size	643355
Page Count	4
File Format	PDF
ISBN	9781467300452
ISSN	15206149
e-ISBN	9781467300469
e-ISBN	9781467300445
DOI	10.1109/ICASSP.2012.6287916
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-03-25
Publisher Place	Japan
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Bayesian methods Abstracts Indexes Continuous wavelet transforms Biological system modeling hierarchical Dirichlet process (HDP) infinite probabilistic context-free grammar (infinite PCFG) nonnegative matrix factorization (NMF) Markov chain Monte Carlo (MCMC)
Content Type	Text
Resource Type	Article

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