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Speech recognition by concatenating fenonic allophone hidden Markov models in parallel among subwords

  • US 5,502,791 A
  • Filed: 09/01/1993
  • Issued: 03/26/1996
  • Est. Priority Date: 09/29/1992
  • Status: Expired due to Fees
First Claim
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1. A speech recognizer comprising:

  • means for analyzing a word inputted as speech for its features and thus obtaining a label sequence or feature vector sequence corresponding to said word;

    means for retaining hidden Markov models respectively for one or more allophones of subwords of each speech transformation candidate;

    dictionary means for retaining a plurality of candidate words to be recognized;

    means for composing a speech model by concatenating each hidden Markov model for allophones of each speech transformation candidate in parallel among subwords in correspondence to a candidate word;

    means for determining a probability of a speech model composed with regard to each candidate word to output the label sequence or feature vector sequence of said word inputted as speech, and outputting the candidate word corresponding to a speech model of a highest probability as a result of recognition.

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