A hierarchical neural network model based on a C/V segmentation algorithm for isolated Mandarin speech recognition

Author

Wang, Jhing-Fa ; Wu, Chung-Hsien ; Chang, Shih-Hung ; Lee, Jau-Yien

Author_Institution

Dept. of Electr. Eng., Nat. Cheng Kung Univ., Tainan, Taiwan

Volume

39

Issue

9

fYear

1991

fDate

9/1/1991 12:00:00 AM

Firstpage

2141

Lastpage

2146

Abstract

A novel algorithm simultaneously performing consonant/vowel (C/V) segmentation and pitch detection is proposed. Based on this algorithm, a consonant enhancement method and a hierarchical neural network scheme are explored for Mandarin speech recognition. As a result, an improvement of 12% in consonant recognition rate is obtained and the number of recognition candidates is reduced from 1300 to 63. A series of experiments over all Mandarin syllables (about 1300) is demonstrated in the speaker-dependent mode. Comparisons with the decoder timer waveform algorithm are evaluated to show that the performance is satisfactory. An overall recognition rate of 90.14% is obtained

Keywords

hierarchical systems; neural nets; speech recognition; C/V segmentation algorithm; consonant enhancement method; consonant recognition rate; consonant/vowel segmentation; hierarchical neural network model; isolated Mandarin speech recognition; performance; pitch detection; speaker-dependent mode; Councils; Degradation; Detection algorithms; Hidden Markov models; Natural languages; Neural networks; Speech recognition; Tin; Vocabulary;

fLanguage

English

Journal_Title

Signal Processing, IEEE Transactions on

Publisher

ieee

ISSN

1053-587X

Type

jour

DOI

10.1109/78.134458

Filename

134458