DocumentCode
2920229
Title
Particle Filter Based Non-Stationary Noise Tracking for Robust Speech Recognition
Author
Fujimoto, Masakiyo ; Nakamura, Satoshi
Author_Institution
ATR Spoken Language Translation Res. Labs., Kyoto, Japan
Volume
1
fYear
2005
fDate
March 18-23, 2005
Firstpage
257
Lastpage
260
Keywords
Monte Carlo methods; hidden Markov models; importance sampling; least mean squares methods; sequential estimation; speech recognition; HMM; MMSE-based clean speech estimation; Markov chain Monte Carlo sampling; Metropolis-Hastings sampling; noise robustness; noise sequence estimation; nonstationary noise tracking; particle filter based speech recognition; residual resampling; sequential importance sampling; sequential noise estimation; speech recognition accuracy; Acoustic noise; Collision mitigation; Hidden Markov models; Monte Carlo methods; Noise robustness; Particle filters; Particle tracking; Speech enhancement; Speech recognition; Working environment noise;
fLanguage
English
Publisher
ieee
Conference_Titel
Acoustics, Speech, and Signal Processing, 2005. Proceedings. (ICASSP '05). IEEE International Conference on
ISSN
1520-6149
Print_ISBN
0-7803-8874-7
Type
conf
DOI
10.1109/ICASSP.2005.1415099
Filename
1415099
Link To Document