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In this contribution to the 3rd CHiME Speech Separation and RecognitionChallenge (CHiME-3) we extend the acoustic front-end of the CHiME-3 baselinespeech recognition system by a coherence-based Wiener filter which is appliedto the output signal of the baseline beamformer. To compute the time- andfrequency-dependent postfilter gains the ratio between direct and diffusesignal components at the output of the baseline beamformer is estimated andused as approximation of the short-time signal-to-noise ratio. The proposedspectral enhancement technique is evaluated with respect to word error rates ofthe CHiME-3 challenge baseline speech recognition system using real speechrecorded in public environments. Results confirm the effectiveness of thecoherence-based postfilter when integrated into the front-end signalenhancement.

Robust coherence-based spectral enhancement for distant speech recognition