Discrete cosine transform particle filter speech enhancement

Authors:
Brady Laska;Miodrag Bolić;Rafik Goubran
Affiliations:
Research in Motion Limited, 4000 Innovation Drive, Ottawa, Ont., Canada K2K 3K1;University of Ottawa, School of Information Technology and Engineering, Ottawa, Ont., Canada K1N 6N5;Department of Systems and Computer Engineering, 1125 Colonel By Drive, Carleton University, Ottawa, Ont., Canada K1S 5B6
Venue:
Speech Communication
Year:
2010

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Abstract

A discrete cosine transform (DCT) domain speech enhancement algorithm is proposed that models the evolution of speech DCT coefficients as a time-varying autoregressive process. Rao-Blackwellized particle filter (RBPF) techniques are used to estimate the model parameters and recover the clean signal coefficients. Using very low-order models for each coefficient and operating at a decimated frame rate, the proposed approach provides a significant complexity reduction compared to the standard full-band RBPF speech enhancement algorithm. In addition to the complexity gains, performance is also improved. Modeling the speech signal in the DCT-domain is shown to provide a better fit in spectral troughs, leading to more noise reduction and less speech distortion. To illustrate possible frequency-dependent processing strategies, a hybrid structure is proposed that offers a complexity/performance trade-off by substituting a simple DCT Wiener filter for the DCT-RBPF in some bands. In comparisons with high performing speech enhancement algorithms using wideband speech and noise, the proposed DCT-RBPF algorithm achieves higher scores on objective quality and intelligibility measures.