Distributed Max-SINR Speech Enhancement with Ad Hoc Microphone Arrays

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Abstract

In recent years, signal processing with ad hoc microphone arrays has attracted a lot of attention. Speech enhancement in noisy, interfered, and reverberant environments is one of the problems targeted by ad hoc microphone arrays. Most of the proposed solutions require knowledge of fingerprints, such as acoustic transfer functions, which may not be known as accurately as required in practical situations. In this paper, a distributed signal subspace filtering method is proposed which is not restricted to a special graph topology. Here, the maximum signal to interference-plus-noise ratio (max-SINR) criterion is used with the primal-dual method of multipliers for distributed filtering. The paper investigates the convergence of the algorithm in both synchronous and asynchronous schemes, and also discusses some practical pros and cons. The applicability of the proposed method is demonstrated by means of simulation results.
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In recent years, signal processing with ad hoc microphone arrays has attracted a lot of attention. Speech enhancement in noisy, interfered, and reverberant environments is one of the problems targeted by ad hoc microphone arrays. Most of the proposed solutions require knowledge of fingerprints, such as acoustic transfer functions, which may not be known as accurately as required in practical situations. In this paper, a distributed signal subspace filtering method is proposed which is not restricted to a special graph topology. Here, the maximum signal to interference-plus-noise ratio (max-SINR) criterion is used with the primal-dual method of multipliers for distributed filtering. The paper investigates the convergence of the algorithm in both synchronous and asynchronous schemes, and also discusses some practical pros and cons. The applicability of the proposed method is demonstrated by means of simulation results.
Original languageEnglish
Title of host publication2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Number of pages5
PublisherIEEE
Publication date2017
Pages151-155
ISBN (Electronic)978-1-5090-4117-6
DOI
StatePublished - 2017
Publication categoryResearch
Peer-reviewedYes
EventThe 42nd IEEE International Conference on Acoustics, Speech and Signal Processing - New Orleans, United States
Duration: 5 Mar 20179 Mar 2017
http://www.ieee-icassp2017.org/
http://www.ieee-icassp2017.org/

Conference

ConferenceThe 42nd IEEE International Conference on Acoustics, Speech and Signal Processing
LandUnited States
ByNew Orleans
Periode05/03/201709/03/2017
Internetadresse
SeriesI E E E International Conference on Acoustics, Speech and Signal Processing. Proceedings
ISSN1520-6149

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ID: 268463694