DocumentCode
2883862
Title
Speaker-independent recognition of isolated Chinese digits by a pyramidical neural net
Author
Yang, Shulin ; Ke, Youan ; Wang, Zhong
Author_Institution
Dept. of Electron. Eng., Beijing Inst. of Technol., China
fYear
1991
fDate
16-17 Jun 1991
Firstpage
45
Abstract
Neural networks have been widely applied to phoneme and word recognition in a speaker-dependent mode. In this paper, a new feature extraction approach, an extended multilayered neural net model and a modified learning algorithm were applied to speaker-independent recognition of isolated Chinese digits. Experiments show that about 85 percent accuracy can be obtained
Keywords
learning systems; neural nets; speech recognition; extended multilayered neural net model; feature extraction; isolated Chinese digits; learning algorithm; phoneme recognition; pyramidical neural net; speaker-independent recognition; word recognition; Computer networks; Data mining; Fault tolerance; Feature extraction; Isolation technology; Multi-layer neural network; Neural networks; Robustness; Speech processing; Speech recognition;
fLanguage
English
Publisher
ieee
Conference_Titel
Circuits and Systems, 1991. Conference Proceedings, China., 1991 International Conference on
Conference_Location
Shenzhen
Type
conf
DOI
10.1109/CICCAS.1991.184276
Filename
184276
Link To Document