Exploiting all combinations of microphone sensors in overdetermined frequency domain blind separation of speech signals

摘要

A new approach to overdetermined frequency domain blind source separation (BSS) of speech signals which exploits all combinations of observations and hence varying inter microphone spacings is proposed. The observations are divided into subgroups so that conventional frequency domain BSS algorithms can be used. By evaluating the separation performance obtained from each group on the basis of approximately measuring the independence of separated signals, the output of the group that has the best performance among all groups on a frequency-by-frequency basis is chosen as the overall output. The separated signals of the overall system are then obtained by transforming their frequency domain representations into the time domain. Simulation results based on speech signals confirm that the proposed approach has better performance based on the performance index (PI) as compared with a conventional scheme using only one microphone group and an existing overdetermined frequency domain BSS algorithm.