Time Frequency Masking Strategy for Blind Source Separation of Acoustic Signals Based on Optimally-Modified LOG-Spectral Amplitude Estimator

Authors:
Eugen Hoffmann;Dorothea Kolossa;Reinhold Orglmeister
Affiliations:
Electronics and Medical Signalprocessing Group, Berlin University of Technology, Berlin, Germany 10587;Electronics and Medical Signalprocessing Group, Berlin University of Technology, Berlin, Germany 10587;Electronics and Medical Signalprocessing Group, Berlin University of Technology, Berlin, Germany 10587
Venue:
ICA '09 Proceedings of the 8th International Conference on Independent Component Analysis and Signal Separation
Year:
2009

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Abstract

The problem of Blind Source Separation (BSS) of convolved acoustic signals is of great interest for many classes of applications such as in-car speech recognition, hands-free telephony or hearing devices. The quality of solutions of ICA algorithms can be improved by applying time-frequency masking . In this paper, a number of time-frequency masking algorithms are compared and a post-processing algorithm is presented that improves the quality of the results of ICA algorithms by applying a modified speech enhancement technique. The proposed method is based on a combination of "classical" time-frequency masking methods and an extended Ephraim-Malah filter. The algorithms have been tested on real-room speech mixtures with a reverberation time of 130 - 159 ms, where a SIR-improvement of up to 23dB has been obtained, which was 11dB above ICA performance for the same dataset.