A robust sound-source separation algorithm for an adverse environment that combines MVDR-PHAT with the CASA framework

Extracting a high-quality speech signal of a single source from a multiple-source input in an adverse environment has always been a challenge for microphone-array processing. Three major approaches have been proposed to tackle this problem: blind-source separation (BSS), beamforming (BF), and comput...

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Bibliographic Details
Published in2011 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA) pp. 273 - 276
Main Authors Hoang Do, Silverman, H. F.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.10.2011
Subjects
Acoustic arrays
acoustic beam steering
Array signal processing
Microphones
Signal processing algorithms
Source separation
Spectrogram
Speech
speech enhancement
Time frequency analysis
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Summary:Extracting a high-quality speech signal of a single source from a multiple-source input in an adverse environment has always been a challenge for microphone-array processing. Three major approaches have been proposed to tackle this problem: blind-source separation (BSS), beamforming (BF), and computational auditory scene analysis (CASA). Combinations of the CASA and BF, BSS and BF also have been introduced. In this paper, we propose a new algorithm which utilizes the null-steering beamformer minimum-variance distortionless response (MVDR) using the proven-robust phase transform (MVDR-PHAT) and the CASA framework that closely mimics human hearing perception. Experimental results using real data recorded in a room with high background and reverberation noise indicated the improved performance of the proposed algorithm compared to those of traditional beamforming algorithms and an SRP-PHAT-based source-separation algorithm recently described at ICASSP 2010.
ISBN:145770692X
9781457706929
ISSN:1931-1168
1947-1629
DOI:10.1109/ASPAA.2011.6082274