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Method for recognizing speech using linguistically-motivated hidden Markov models

  • US 5,268,990 A
  • Filed: 01/31/1991
  • Issued: 12/07/1993
  • Est. Priority Date: 01/31/1991
  • Status: Expired due to Term
First Claim
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1. A method for modeling word-initial acoustic cross-word effects for use in generating word pronunciation networks from a set of pronunciation rules and a training database on a data processing apparatus, wherein said training database comprises representations of speech signals of words being pronounced in a continuous speech manner, said speech signal representations being linked to textual representations of said words, wherein word pronunciation networks include textual representations of words and corresponding phonetic networks, said modeling method comprising the steps, for every word network w, of:

  • for every initial arc ai, setting a variable pi equal to a phone label on said arc ai ; and

    for every phone label pj in a phonetic inventory,a) counting a number of occurrences c in said training database of the word w preceded by any word ending with said phone pj ;

    thereafterb) if c is greater than a preselected threshold,i) adding an initial arc ak to said word network w with phone label pi which connects to a common "to-node"[as said arc ai ;

    thereafterii) constraining said arc ak to only connect to arcs with label pj ; and

    iii) constraining said arc ai not to connect to arcs having phone label pj.

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