Title :
Frequency-Domain Normalized Multichannel Blind Deconvolution for Convolutive Speech Mixtures: Modifications and Properties
Author_Institution :
Dept. of Electron. Eng., Paichai Univ., Daejeon
Abstract :
The normalized multichannel blind deconvolution algorithm and its modifications are described in detail. The proposed algorithm is shown to have fast uniform convergence and improved separation performances for nonstationary sources. In addition, the local stability problem, which limits the separation performance of the algorithm, is investigated in conjunction with source-microphone geometry. Then local stability is treated by decomposing the mixed signals into into direct and reverberant parts. Cascading a beamformer and blind source separation with causal filters is proposed as a practical method to improve local stability. Simulation results using real-world recordings confirm the theoretical expectations.
Keywords :
blind source separation; deconvolution; frequency-domain analysis; microphones; speech processing; stability; beamformer; blind source separation; causal filters; convolutive speech mixtures; frequency-domain normalized multichannel blind deconvolution; local stability problem; nonstationary source separation; source-microphone geometry; uniform convergence; Array signal processing; Blind source separation; Convergence; Deconvolution; Filters; Geometry; Microphones; Source separation; Speech; Stability;
Conference_Titel :
Machine Learning for Signal Processing, 2006. Proceedings of the 2006 16th IEEE Signal Processing Society Workshop on
Conference_Location :
Arlington, VA
Print_ISBN :
1-4244-0656-0
Electronic_ISBN :
1551-2541
DOI :
10.1109/MLSP.2006.275566