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Method for creating and using multiple-word sound models in speech recognition

  • US 4,837,831 A
  • Filed: 10/15/1986
  • Issued: 06/06/1989
  • Est. Priority Date: 10/15/1986
  • Status: Expired due to Fees
First Claim
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1. A prefiltering method for use in a speech recognition system, said method comprising:

  • receiving an acoustic description of an utterance to be recognized;

    storing a vocabulary of words;

    storing a plurality of probabilistic acoustic cluster models and using individual ones of said acoustic cluster models to represent at least a part of more than one vocabulary word;

    comparing at least a portion of said acoustic description from said utterance against each of said cluster models, and producing a cluster likelihood score for each cluster model against which such a comparison is made;

    using the cluster likelihood score produced for each cluster model to calculate a prefilter score for words represented by that cluster model; and

    selecting a subset of said vocabulary words to undergo a more lengthy comparison against said utterance to be recognized based on the prefilter scores associated with said vocabulary words;

    wherein;

    said acoustic description of said utterance to be recognized includes a succession of acoustic descriptions representing a sequence of sounds associated with said utterance;

    said cluster models each comprises a succession of probabilistic acoustic models, for modeling a sequence of sounds associated with each word represented by said cluster model;

    said comparing includes comparing a succession of said acoustic descriptions from the utterance to be recognized against the succession of acoustic models from each of a plurality of cluster models and producing a cluster likelihood score for each such cluster model as a result of that comparison; and

    said cluster models are wordstart cluster models, that is, models which only represent the initial portion of many words in said vocabulary.

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