Scale-invariant probabilistic latent component analysis

Romain Hennequin; Roland Badeau; Bertrand David

doi:10.1109/ASPAA.2011.6082265

Scale-invariant probabilistic latent component analysis

Romain Hennequin, Roland Badeau, Bertrand David

CNRS LTCI

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

In this paper, we present a new method for decomposing musical spectrograms. This method is similar to shift-invariant Probabilistic Latent Component Analysis, but, when the latter works with constant Q spectrograms (i.e. with a logarithmic frequency resolution), our technique is designed to decompose standard short time Fourier transform spectrograms (i.e. with a linear frequency resolution). This makes it possible to easily reconstruct the latent signals (which can be useful for source separation).

Original language	English
Title of host publication	2011 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, WASPAA 2011
Pages	129-132
Number of pages	4
DOIs	https://doi.org/10.1109/ASPAA.2011.6082265
Publication status	Published - 19 Dec 2011
Externally published	Yes
Event	2011 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, WASPAA 2011 - New Paltz, NY, United States Duration: 16 Oct 2011 → 19 Oct 2011

Publication series

Name	IEEE Workshop on Applications of Signal Processing to Audio and Acoustics

Conference

Conference	2011 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, WASPAA 2011
Country/Territory	United States
City	New Paltz, NY
Period	16/10/11 → 19/10/11

Keywords

Music signal processing
non-negative matrix factorization
probabilistic latent component analysis
shiftinvariant decomposition

Access to Document

10.1109/ASPAA.2011.6082265

Cite this

@inproceedings{1ca73fe2ed4e4b858a4a8e157e8273f3,

title = "Scale-invariant probabilistic latent component analysis",

abstract = "In this paper, we present a new method for decomposing musical spectrograms. This method is similar to shift-invariant Probabilistic Latent Component Analysis, but, when the latter works with constant Q spectrograms (i.e. with a logarithmic frequency resolution), our technique is designed to decompose standard short time Fourier transform spectrograms (i.e. with a linear frequency resolution). This makes it possible to easily reconstruct the latent signals (which can be useful for source separation).",

keywords = "Music signal processing, non-negative matrix factorization, probabilistic latent component analysis, shiftinvariant decomposition",

author = "Romain Hennequin and Roland Badeau and Bertrand David",

year = "2011",

month = dec,

day = "19",

doi = "10.1109/ASPAA.2011.6082265",

language = "English",

isbn = "9781457706912",

series = "IEEE Workshop on Applications of Signal Processing to Audio and Acoustics",

pages = "129--132",

booktitle = "2011 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, WASPAA 2011",

note = "2011 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, WASPAA 2011 ; Conference date: 16-10-2011 Through 19-10-2011",

}

Hennequin, R, Badeau, R & David, B 2011, Scale-invariant probabilistic latent component analysis. in 2011 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, WASPAA 2011., 6082265, IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, pp. 129-132, 2011 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, WASPAA 2011, New Paltz, NY, United States, 16/10/11. https://doi.org/10.1109/ASPAA.2011.6082265

Scale-invariant probabilistic latent component analysis. / Hennequin, Romain; Badeau, Roland; David, Bertrand.
2011 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, WASPAA 2011. 2011. p. 129-132 6082265 (IEEE Workshop on Applications of Signal Processing to Audio and Acoustics).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Scale-invariant probabilistic latent component analysis

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AU - Badeau, Roland

AU - David, Bertrand

PY - 2011/12/19

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N2 - In this paper, we present a new method for decomposing musical spectrograms. This method is similar to shift-invariant Probabilistic Latent Component Analysis, but, when the latter works with constant Q spectrograms (i.e. with a logarithmic frequency resolution), our technique is designed to decompose standard short time Fourier transform spectrograms (i.e. with a linear frequency resolution). This makes it possible to easily reconstruct the latent signals (which can be useful for source separation).

AB - In this paper, we present a new method for decomposing musical spectrograms. This method is similar to shift-invariant Probabilistic Latent Component Analysis, but, when the latter works with constant Q spectrograms (i.e. with a logarithmic frequency resolution), our technique is designed to decompose standard short time Fourier transform spectrograms (i.e. with a linear frequency resolution). This makes it possible to easily reconstruct the latent signals (which can be useful for source separation).

KW - Music signal processing

KW - non-negative matrix factorization

KW - probabilistic latent component analysis

KW - shiftinvariant decomposition

U2 - 10.1109/ASPAA.2011.6082265

DO - 10.1109/ASPAA.2011.6082265

M3 - Conference contribution

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T3 - IEEE Workshop on Applications of Signal Processing to Audio and Acoustics

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Y2 - 16 October 2011 through 19 October 2011

ER -

Scale-invariant probabilistic latent component analysis

Abstract

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Keywords

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