Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Speech Source Separation in Convolutive Environments Using Space-Time-Frequency Analysis | Hindawi Publishing Corporation EURASIP Journal on Applied Signal Processing Volume 2006 Article ID 38412 Pages 1-11 DOI ASP 2006 38412 Speech Source Separation in Convolutive Environments Using Space-Time-Frequency Analysis Shlomo Dubnov 1 Joseph Tabrikian 2 and Miki Arnon-Targan2 1 CALIT 2 University of California San Diego CA 92093 USA 2 Department of Electrical and Computer Engineering Ben-Gurion University of the Negev Beer-Sheva 84105 Israel Received 10 February 2005 Revised 28 September 2005 Accepted 4 October 2005 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. Copyright 2006 Shlomo Dubnov et al. 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. 1. INTRODUCTION Many audio communication and entertainment applications deal with acoustic signals that contain combinations of several acoustic sources in a mixture that overlaps in time and frequency. In the recent years there has been a growing interest in methods that are capable of separating audio signals from microphone arrays using blind source separation BSS techniques 1 . In contrast to most of the research works in BSS .
