Broadband Deterministic Blind Beamforming for Speech Separation Using Microphone Arrays via Rotational Invariance Techniques

In this paper a novel approach for speech separation using microphone arrays is presented. It belongs to the class of deterministic blind beamforming (DBBF) approaches via rotational invariance techniques. Since speech should be considered as broadband sources in microphone array related application...

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Bibliographic Details
Published in2006 International Conference on Communications, Circuits and Systems Vol. 1; pp. 271 - 275
Main Authors Lin Jing-Ran, Peng Qi-Cong
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.06.2006
Subjects
Array signal processing
Blind source separation
Error analysis
Frequency domain analysis
Microphone arrays
Narrowband
Sensor arrays
Source separation
Speech
Vectors
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Summary:In this paper a novel approach for speech separation using microphone arrays is presented. It belongs to the class of deterministic blind beamforming (DBBF) approaches via rotational invariance techniques. Since speech should be considered as broadband sources in microphone array related applications, the conventional narrowband DBBF is extended to broadband cases in this paper. Utilizing the nonstationarity of speech, DBBF is implemented at the frequency bins of interest. In order to cope with the problem of channel swap, a rearranging operation is performed, based on the correlation coefficients between the frequency domain separated sequences of adjacent bins. Moreover, the scale ambiguity, another drawback of the general blind source separation approaches, is also eliminated in this paper. Numerical examples confirm the effectiveness of the proposed approach
ISBN:9780780395848
0780395840
DOI:10.1109/ICCCAS.2006.284633