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Cepstral Weighting for Speech Dereverberation Without Musical Noise
KTH, School of Electrical Engineering (EES), Sound and Image Processing.
2011 (English)In: Proceedings European Signal Processing Conference, 2011, 2309-2313 p.Conference paper (Refereed)
Abstract [en]

We present an effective way to reduce musical noise in binaural speech dereverberation algorithms based on an instantaneous weighting of the cepstrum. We propose this instantaneous technique, as temporal smoothing techniques result ina smearing of the signal over time and are thus expected to reduce the dereverberation performance. For the instantaneousweighting function we compute the a posteriori probabilitythat a cepstral coefficient represents the speech spectral structure. The proposed algorithm incorporates a priori knowledge about the speech spectral structure by training the parameters of the respective likelihood function offline using aspeech database. The proposed algorithm employs neither avoiced/unvoiced detection nor a fundamental period estimator and is shown to outperform an algorithm without cepstralprocessing in terms of a higher signal-to-interference ratio, alower bark spectral distortion, and a lower log kurtosis ratio, indicating a reduction of musical noise.

Place, publisher, year, edition, pages
2011. 2309-2313 p.
National Category
Signal Processing
URN: urn:nbn:se:kth:diva-42718ScopusID: 2-s2.0-84863742389OAI: diva2:447542
European Signal Processing Conference
QC 20111014Available from: 2011-10-12 Created: 2011-10-12 Last updated: 2011-10-14Bibliographically approved

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