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Discrete Cosine Transform Particle Filter Speech Enhancement by Brady Laska; Miodrag Bolić; Rafik Goubran is a Computer Science article available to read on EtoBox.

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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 frequencydependent 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.

Who reads Discrete Cosine Transform Particle Filter Speech Enhancement?

Author

Brady Laska; Miodrag Bolić; Rafik Goubran

Publisher

Elsevier Science; Elsevier ; Elsevier BV (ISSN 0167-6393)

Published

2010

Language

EN

Field

Computer Science (Physical Sciences)