Isolated Mandarin base-syllable recognition based upon the segmentai probability model

Ren Yuan Lyu*, I. Chung Hong, Jia Lin Shen, Ming Yu Lee, Lin Shan Lee

*Corresponding author for this work

Research output: Contribution to journalJournal Article peer-review

9 Scopus citations

Abstract

In this correspondence, a segmental probability model (SPM) is proposed for fast and accurate recognition of the highly confusing isolated Mandarin base-syllables by deleting the state transition probabilities of continuous density hidden Markov models (CHMM), abandoning the dynamic programming process, letting the states equally segment the base-syllables deterministically, and using several special approaches to improve the accuracy and speed. This is achieved by considering the special characteristics of the target vocabulary.

Original languageEnglish
Pages (from-to)293-299
Number of pages7
JournalIEEE Transactions on Speech and Audio Processing
Volume6
Issue number3
DOIs
StatePublished - 1998

Keywords

  • Hidden markov model
  • Isolated syllable
  • Mandarin chinese
  • Segmental probability model
  • Speech recognition

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