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Codebook-based Bayesian speech enhancement
KTH, School of Electrical Engineering (EES), Sound and Image Processing.
KTH, School of Electrical Engineering (EES), Sound and Image Processing.
KTH, School of Electrical Engineering (EES), Sound and Image Processing.
2005 (English)In: 2005 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING, 2005, 1077-1080 p.Conference paper (Refereed)
Abstract [en]

In this paper, we propose a Bayesian approach for the estimation of the short-term predictor parameters of speech and noise, from the noisy observation. The resulting estimates of the speech and noise spectra can be used in a Wiener filter or any state-of-the-art speech enhancement system. We utilize a-priori information about both speech and noise in the form of trained codebooks of linear predictive coefficients. In contrast to current Bayesian estimation approaches that consider the excitation variances as part of the a-priori information, in the proposed method they are computed analytically based on the observation at hand. Consequently, the method performs well in nonstationary noise conditions. Experimental results confirm the superior performance of the proposed method compared to existing Bayesian approaches, such as those based on hidden Markov models.

Place, publisher, year, edition, pages
2005. 1077-1080 p.
, International Conference on Acoustics Speech and Signal Processing ICASSP, ISSN 1520-6149
National Category
Computer and Information Science
URN: urn:nbn:se:kth:diva-36148DOI: 10.1109/ICASSP.2005.1415304ISI: 000229404200270ScopusID: 2-s2.0-33645821784OAI: diva2:430462
30th IEEE International Conference on Acoustics, Speech, and Signal Processing Philadelphia, PA, MAR 19-23, 2005
QC 20110711Available from: 2011-07-11 Created: 2011-07-08 Last updated: 2011-10-14Bibliographically approved

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Srinivasan, SriramSamuelsson, JonasKleijn, W. Bastiaan
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