DocumentCode :
3530225
Title :
Stereo-based stochastic noise compensation based on trajectory GMMS
Author :
Zen, Heiga ; Nankaku, Yoshihiko ; Tokuda, Keiichi
Author_Institution :
Dept. of Comput. Sci., Nagoya Inst. of Technol., Nagoya
fYear :
2009
fDate :
19-24 April 2009
Firstpage :
4577
Lastpage :
4580
Abstract :
This paper proposes a novel stereo-based stochastic noise compensation technique based on trajectory GMMs. Although the GMM-based noise compensation techniques such as SPLICE work effective, their performance sometimes degrades due to the inappropriate dynamic characteristics caused by the frame-by-frame mapping. While the use of dynamic feature constraints on the mapping stage can alleviate this problem, it also introduces an inconsistency between training and mapping. The recently proposed trajectory GMM-based feature mapping technique can solve this inconsistency while keeping the benefits of the use of dynamic features, and offers an entire sequence-level transformation rather than the frame-by-frame mapping. Results from a noise compensation experiment on the AURORA-2 task show that the proposed trajectory GMM-based noise compensation technique outperforms the conventional ones.
Keywords :
Gaussian noise; speech recognition; Gaussian mixture models; feature mapping technique; speech recognition; stereo-based stochastic noise compensation; trajectory GMMS; Computer science; Degradation; Gaussian noise; Hidden Markov models; Mel frequency cepstral coefficient; Probability density function; Speech recognition; Statistics; Stochastic resonance; Trajectory; GMM-based mapping; dynamic features; noise compensation; speech recognition; trajectory GMM;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Acoustics, Speech and Signal Processing, 2009. ICASSP 2009. IEEE International Conference on
Conference_Location :
Taipei
ISSN :
1520-6149
Print_ISBN :
978-1-4244-2353-8
Electronic_ISBN :
1520-6149
Type :
conf
DOI :
10.1109/ICASSP.2009.4960649
Filename :
4960649
Link To Document :
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