Publication Type |
Journal Article |
School or College |
College of Engineering |
Department |
Electrical & Computer Engineering |
Creator |
Mathews, V. John |
Other Author |
Deng, Ying |
Title |
Subband particle filtering for speech enhancement |
Date |
2006 |
Description |
ABSTRACT Particle filters have recently been applied to speech enhancement when the input speech signal is modeled as a time-varying autoregressive process with stochastically evolving parameters. This type of modeling results in a nonlinear and conditionally Gaussian statespace system that is not amenable to analytical solutions. Prior work in this area involved signal processing in the fullband domain and assumed white Gaussian noise with known variance. This paper extends such ideas to subband domain particle filters and colored noise. Experimental results indicate that the subband particle filter achieves higher segmental SNR than the fullband algorithm and is effective in dealing with colored noise without increasing the computational complexity. |
Type |
Text |
Publisher |
Institute of Electrical and Electronics Engineers (IEEE) |
First Page |
4 |
Last Page |
8 |
Language |
eng |
Bibliographic Citation |
Deng, Y., & Mathews, V. J. (2006). Subband particle filtering for speech enhancement. Proc. Fourteenth European Signal Processing Conference. September 4-8. |
Rights Management |
(c)2006 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. |
Format Medium |
application/pdf |
Format Extent |
627,058 bytes |
Identifier |
ir-main,15183 |
ARK |
ark:/87278/s61551hk |
Setname |
ir_uspace |
ID |
706036 |
Reference URL |
https://collections.lib.utah.edu/ark:/87278/s61551hk |