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Speech Source Separation in Convolutive Environments Using Space-Time-Frequency Analysis

  • Shlomo Dubnov1,
  • Joseph Tabrikian2 and
  • Miki Arnon-Targan2
EURASIP Journal on Advances in Signal Processing20062006:038412

Received: 10 February 2005

Accepted: 4 October 2005

Published: 15 May 2006


We propose a new method for speech source separation that is based on directionally-disjoint estimation of the transfer functions between microphones and sources at different frequencies and at multiple times. The spatial transfer functions are estimated from eigenvectors of the microphones' correlation matrix. Smoothing and association of transfer function parameters across different frequencies are performed by simultaneous extended Kalman filtering of the amplitude and phase estimates. This approach allows transfer function estimation even if the number of sources is greater than the number of microphones, and it can operate for both wideband and narrowband sources. The performance of the proposed method was studied via simulations and the results show good performance.


Information TechnologyTransfer FunctionCorrelation MatrixMultiple TimeQuantum Information


Authors’ Affiliations

CALIT 2, University of California, San Diego, USA
Department of Electrical and Computer Engineering, Ben-Gurion University of the Negev, Beer-Sheva, Israel


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© Shlomo Dubnov et al. 2006

This article is published under license to BioMed Central Ltd. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.