DocumentCode :
290371
Title :
A hierarchical LPNN network for noise reduction and noise degraded speech recognition
Author :
Gao, Yuqing ; Haton, Jean Paul
Author_Institution :
Apple-ISS Res. Center, Inst. of Syst. Sci., Singapore
Volume :
ii
fYear :
1994
fDate :
19-22 Apr 1994
Abstract :
We present a new linked predictive neural network structure-hierarchical LPNN-and the speech recognition system based on it. This neural network is specially developed for the noise degraded speech recognition problem and integrates the speech recognition and noise reduction in a unified structure. The network is trained according to joint optimization criterion both for the signal prediction and for the noise reduction. We present results which indicate that joint optimization results in a better speech recognition performance of the all over system for noise degraded speech signals
Keywords :
learning (artificial intelligence); neural nets; noise; optimisation; prediction theory; speech enhancement; speech recognition; hierarchical LPNN network; joint optimization; linked predictive neural network; noise degraded speech recognition; noise degraded speech signal; noise reduction; signal prediction; speech enhancement; speech recognition performance; speech recognition system; Data preprocessing; Degradation; Multilayer perceptrons; Neural networks; Noise reduction; Speech enhancement; Speech recognition; System testing; Training data; Vocabulary;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Acoustics, Speech, and Signal Processing, 1994. ICASSP-94., 1994 IEEE International Conference on
Conference_Location :
Adelaide, SA
ISSN :
1520-6149
Print_ISBN :
0-7803-1775-0
Type :
conf
DOI :
10.1109/ICASSP.1994.389711
Filename :
389711
Link To Document :
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