A Hierarchical Neural Network Model Based On A C/V Segmentation Algorithm For Isolated Mandarin Speech Recognition

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

Research output: Contribution to journalArticle

51 Citations (Scopus)

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) are demonstrated in the speaker-dependent mode. Comparisons with the DTW algorithm are evaluated to show that the performance is satisfactory. An overall recognition rate of 90.14% is obtained.

Original languageEnglish
Pages (from-to)2141-2146
Number of pages6
JournalIEEE Transactions on Signal Processing
Volume39
Issue number9
DOIs
Publication statusPublished - 1991 Sep

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Electrical and Electronic Engineering

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