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CSL
2016
Springer

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

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Application of continuous state Hidden Markov Models to a classical problem in speech recognition
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, Language and Speech 7 (1964)).
Colin J. Champion, S. M. Houghton
Added 01 Apr 2016
Updated 01 Apr 2016
Type Journal
Year 2016
Where CSL
Authors Colin J. Champion, S. M. Houghton
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