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Speech recognition incorporating a priori probability weighting factors

  • US 5,999,902 A
  • Filed: 07/16/1997
  • Issued: 12/07/1999
  • Est. Priority Date: 03/07/1995
  • Status: Expired due to Term
First Claim
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1. A method of speech recognition comprising the steps of:

  • comparing a portion of an unknown utterance with reference models to generate a measure of similarity;

    repetitively comparing further portions of the unknown utterance with reference models to generate, for each of a plurality of allowable sequences of reference models defined by stored data defining such sequences, accumulated measures of similarity including contributions from previously generated measures obtained from comparison of one or more earlier portions of the utterance with a reference model or models in the respective allowable sequence; and

    weighting the accumulated measures in accordance with predetermined weighting factors representing an a priori probability for each of the allowable sequences wherein the weighting step is performed by weighting each computation of a measure or accumulated measure for a partial sequence by combined values of the weighting factors for each of the allowable sequences which commences with that partial sequence, modified by any such combined values of the weighting factors applied to a measure generated in respect of a shorter sequence with which that partial sequence commences.

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