Fast and simple iterative algorithm of Lp-norm minimization for under-determined speech separation

Yasuharu Hirasawa; Naoki Yasuraoka; Toru Takahashi; Tetsuya Ogata; Hiroshi G. Okuno

Fast and simple iterative algorithm of Lp-norm minimization for under-determined speech separation

Yasuharu Hirasawa^*, Naoki Yasuraoka, Toru Takahashi, Tetsuya Ogata, Hiroshi G. Okuno

^*Corresponding author for this work

Research output: Contribution to journal › Conference article › peer-review

Abstract

This paper presents an efficient algorithm to solve Lp-norm minimization problem for under-determined speech separation; that is, for the case that there are more sound sources than microphones. We employ an auxiliary function method in order to derive update rules under the assumption that the amplitude of each sound source follows generalized Gaussian distribution. Experiments reveal that our method solves the L1-norm minimization problem ten times faster than a general solver, and also solves Lp-norm minimization problem efficiently, especially when the parameter p is small; when p is not more than 0.7, it runs in real-time without loss of separation quality.

Original language	English
Pages (from-to)	1745-1748
Number of pages	4
Journal	Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH
Publication status	Published - 2011 Dec 1
Externally published	Yes
Event	12th Annual Conference of the International Speech Communication Association, INTERSPEECH 2011 - Florence, Italy Duration: 2011 Aug 27 → 2011 Aug 31

Keywords

Auxiliary function method
Lp-norm minimization
Speech separation
Under-determined condition

ASJC Scopus subject areas

Language and Linguistics
Human-Computer Interaction
Signal Processing
Software
Modelling and Simulation

Cite this

Fast and simple iterative algorithm of Lp-norm minimization for under-determined speech separation. / Hirasawa, Yasuharu; Yasuraoka, Naoki; Takahashi, Toru et al.

In: Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH, 01.12.2011, p. 1745-1748.

Research output: Contribution to journal › Conference article › peer-review

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title = "Fast and simple iterative algorithm of Lp-norm minimization for under-determined speech separation",

abstract = "This paper presents an efficient algorithm to solve Lp-norm minimization problem for under-determined speech separation; that is, for the case that there are more sound sources than microphones. We employ an auxiliary function method in order to derive update rules under the assumption that the amplitude of each sound source follows generalized Gaussian distribution. Experiments reveal that our method solves the L1-norm minimization problem ten times faster than a general solver, and also solves Lp-norm minimization problem efficiently, especially when the parameter p is small; when p is not more than 0.7, it runs in real-time without loss of separation quality.",

keywords = "Auxiliary function method, Lp-norm minimization, Speech separation, Under-determined condition",

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AU - Hirasawa, Yasuharu

AU - Yasuraoka, Naoki

AU - Takahashi, Toru

AU - Ogata, Tetsuya

AU - Okuno, Hiroshi G.

PY - 2011/12/1

Y1 - 2011/12/1

N2 - This paper presents an efficient algorithm to solve Lp-norm minimization problem for under-determined speech separation; that is, for the case that there are more sound sources than microphones. We employ an auxiliary function method in order to derive update rules under the assumption that the amplitude of each sound source follows generalized Gaussian distribution. Experiments reveal that our method solves the L1-norm minimization problem ten times faster than a general solver, and also solves Lp-norm minimization problem efficiently, especially when the parameter p is small; when p is not more than 0.7, it runs in real-time without loss of separation quality.

AB - This paper presents an efficient algorithm to solve Lp-norm minimization problem for under-determined speech separation; that is, for the case that there are more sound sources than microphones. We employ an auxiliary function method in order to derive update rules under the assumption that the amplitude of each sound source follows generalized Gaussian distribution. Experiments reveal that our method solves the L1-norm minimization problem ten times faster than a general solver, and also solves Lp-norm minimization problem efficiently, especially when the parameter p is small; when p is not more than 0.7, it runs in real-time without loss of separation quality.

KW - Auxiliary function method

KW - Lp-norm minimization

KW - Speech separation

KW - Under-determined condition

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JO - Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH

JF - Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH

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Y2 - 27 August 2011 through 31 August 2011

ER -

Fast and simple iterative algorithm of Lp-norm minimization for under-determined speech separation

Abstract

Keywords

ASJC Scopus subject areas

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