| Paper: | SPTM-P12.1 | ||
| Session: | Estimation | ||
| Time: | Friday, May 21, 13:00 - 15:00 | ||
| Presentation: | Poster | ||
| Topic: | Signal Processing Theory and Methods: Detection, Estimation, and Class. Thry & Apps. | ||
| Title: | BLIND DECONVOLUTION USING BAYESIAN METHODS WITH APPLICATION TO THE DEREVERBERATION OF SPEECH | ||
| Authors: | Michael J. Daly; McMaster University | ||
| James P. Reilly; McMaster University | |||
| Abstract: | A blind deconvolution algorithm is presented to address theproblem of the dereverberation of speech. A Bayesian algorithm isdeveloped for estimating the source, and the problem ofill-conditioning due to long tails of an acoustic impulse response (AIR) is avoided by marginalizing out the unknown channel parameters. The initial samples of the MAP estimate are determined using a stochastic MCMC technique, and these estimates are then used in a sequential procedure for estimating the remaining of the signal. A filterbank implementation is used to reduce the large deconvolution problem into several smaller independent problems. Simulation results are presented to demonstrate the performance of the algorithm applied to the dereverberation of speech. | ||
| Back | |||
Home -||-
Organizing Committee -||-
Technical Committee -||-
Technical Program -||-
Plenaries
Paper Submission -||-
Special Sessions -||-
ITT -||-
Paper Review -||-
Exhibits -||-
Tutorials
Information -||-
Registration -||-
Travel Insurance -||-
Housing -||-
Workshops