Cochannel speech separation.

C K Lee; D G Childers

doi:10.1121/1.396429

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Cochannel speech separation.

C K Lee·D G Childers

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Abstract

The multisignal minimum-cross-entropy spectral analysis (multisignal MCESA) is applied to the problem of separating the speech signals of two talkers speaking simultaneously on a single channel, e.g., when two talkers use a single microphone. A new two-stage approach to the problem is proposed in which a spectral separator is followed by a spectral tailoring procedure. The spectral separator produces an initial estimate of the speech spectrum for each talker. Then the spectral tailoring procedure employs the multisignal MCESA technique to adjust the initial spectral estimates to account for the characteristics of the known cochannel composite speech signal. The research emphasis is placed on the implementation and evaluation of the spectral tailoring procedure, i.e., the use of the multisignal MCESA in the proposed scheme. Its usefulness is evaluated and validated by listening tests and by comparing the spectral distortions of the estimated voices before and after the multisignal MCESA processing.

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Algorithms Female Humans Male Models, Psychological Speech Acoustics Speech Perception Journal Article Research Support, Non-U.S. Gov't Research Support, U.S. Gov't, Non-P.H.S.

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C K Lee, D G Childers. 1988. Cochannel speech separation.. https://doi.org/10.1121/1.396429

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