DocumentCode :
178066
Title :
Reverberation and noise robust feature enhancement using multiple inputs
Author :
Shin Jae Kang ; Tae Gyoon Kang ; Kang Hyun Lee ; Kiho Cho ; Nam Soo Kim
Author_Institution :
Dept. of Electr. & Comput. Eng., Seoul Nat. Univ., Seoul, South Korea
fYear :
2014
fDate :
4-9 May 2014
Firstpage :
1740
Lastpage :
1744
Abstract :
We propose a novel approach to feature enhancement in multi-channel scenario. Our approach is based on the interacting multiple model (IMM), which was originally developed in single-channel scenario. We extend the single-channel IMM algorithm such that it can handle the multichannel inputs under the Bayesian framework. The multichannel IMM algorithm is capable of tracking time-varying room impulse responses and background noises by updating the relevant parameters in an on-line manner. In various environmental conditions, the performance gain of the proposed method has been confirmed.
Keywords :
Bayes methods; acoustic signal processing; feature extraction; reverberation; speech recognition; target tracking; time-varying channels; transient response; Bayesian framework; automatic speech recognition; background noise; interacting multiple model; multichannel IMM algorithm; noise robust feature enhancement; reverberation; single channel IMM algorithm; time-varying room impulse response tracking; Microphones; Noise measurement; Reverberation; Speech; Speech recognition; Vectors; Robust speech recognition; dereverberation; interacting multiple model (IMM); multi-channel;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Acoustics, Speech and Signal Processing (ICASSP), 2014 IEEE International Conference on
Conference_Location :
Florence
Type :
conf
DOI :
10.1109/ICASSP.2014.6853896
Filename :
6853896
Link To Document :
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