New EM algorithms for source separation and deconvolution with a microphone array

This paper presents new algorithms for source separation with a microphone array. Key to our algorithms are exploiting detailed source models, using subband filtering ideas to model the reverberant environment, and employing explicit models for background and sensor noise. We demonstrate strong perf...

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Bibliographic Details
Published in2003 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03) Vol. 5; pp. V - 297
Main Author Attias, H.
Format Conference Proceeding
LanguageEnglish
Published IEEE 2003
Subjects
Background noise
Deconvolution
Filtering algorithms
Machine learning
Machine learning algorithms
Microphone arrays
Noise robustness
Reverberation
Source separation
Working environment noise
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ISBN9780780376632
0780376633
ISSN1520-6149
DOI10.1109/ICASSP.2003.1199930

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Summary:This paper presents new algorithms for source separation with a microphone array. Key to our algorithms are exploiting detailed source models, using subband filtering ideas to model the reverberant environment, and employing explicit models for background and sensor noise. We demonstrate strong performance which is robust to noise and reverberations. Good scaling properties are obtained using machine learning techniques.
ISBN:9780780376632
0780376633
ISSN:1520-6149
DOI:10.1109/ICASSP.2003.1199930