Application of continuous state Hidden Markov Models to a classical problem in speech recognition

Colin Champion, Stephen Houghton

Research output: Contribution to journalArticlepeer-review

18 Citations (Scopus)
180 Downloads (Pure)

Abstract

This paper describes an optimal algorithm using continuous state Hidden Markov Models for solving the HMS decoding problem, which is the problem of recovering an underlying sequence of phonetic units from measurements of smoothly varying acoustic features, thus inverting the speech generation process described by Holmes, Mattingly and Shearme in a well known paper (Speech synthesis by rule. Lang. Speech 7 (1964)).
Original languageEnglish
Pages (from-to)347-364
JournalComputer Speech and Language
Volume36
Early online date14 May 2015
DOIs
Publication statusPublished - Mar 2016

Keywords

  • Speech recognition
  • Hidden Markov Model
  • Recognition by synthesis

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