Presentation | 2012-11-07 Infinite Composite Autoregressive Models based on Gamma Processes for Music Signal Analysis Kazuyoshi YOSHII, Masataka GOTO, |
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Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | This paper presents novel statistical models that can be used for multiple fundamental frequency (F0) estimation and timbre-based source separation of polyphonic music signals. These models are based on nonnegative matrix factorization (NMF) extended by the source-filter paradigm, in which an amplitude or power spectrogram is decomposed as the product of two kinds of spectral atoms (sources and filters) and time-varying gains of source-filter pairs. However, a critical problem is that the numbers of sources and filters should be given in advance. To solve this problem, we propose nonparametric Bayesian models based on gamma processes and efficient variational and multiplicative learning algorithms. These infinite composite autoregressive models (iCARMs) can discover effective numbers of sources and filters in a data-driven manner. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | Music signal analysis / F0 estimation / source separation / gamma process / nonparametric Bayes |
Paper # | IBISML2012-51 |
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Committee | IBISML |
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Conference Date | 2012/10/31(1days) |
Place (in Japanese) | (See Japanese page) |
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Registration To | Information-Based Induction Sciences and Machine Learning (IBISML) |
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Language | JPN |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | Infinite Composite Autoregressive Models based on Gamma Processes for Music Signal Analysis |
Sub Title (in English) | |
Keyword(1) | Music signal analysis |
Keyword(2) | F0 estimation |
Keyword(3) | source separation |
Keyword(4) | gamma process |
Keyword(5) | nonparametric Bayes |
1st Author's Name | Kazuyoshi YOSHII |
1st Author's Affiliation | National Institute of Advanced Industrial Science and Technology (AIST)() |
2nd Author's Name | Masataka GOTO |
2nd Author's Affiliation | National Institute of Advanced Industrial Science and Technology (AIST) |
Date | 2012-11-07 |
Paper # | IBISML2012-51 |
Volume (vol) | vol.112 |
Number (no) | 279 |
Page | pp.pp.- |
#Pages | 8 |
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