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Speech recognition system utilizing pre-calculated similarity measurements

  • US 5,546,499 A
  • Filed: 05/27/1994
  • Issued: 08/13/1996
  • Est. Priority Date: 05/27/1994
  • Status: Expired due to Term
First Claim
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1. A method of preparing a compressed matrix of precalculated distance metrics for comparing an input utterance which is represented by a sequence of prototype data frames selected from a preselected set of prototype data frames with at least some of a vocabulary of word models each of which is represented by a sequence of prototype states selected from a preselected set of prototype states, said method comprising:

  • generating an array of distance metrics for all combinations of prototype frames and prototype states;

    for each state, identifying the frames for which the corresponding metric is meaningful;

    for each state, determining a common default value for non-meaningful metrics;

    for at least one group of frames corresponding to each state, determining the locations within said array containing meaningful metrics;

    building a combined list of meaningful metrics by adding the meaningful metrics from successive groups of frames using an offset for each group which allows the meaningful metrics for each group to fit into currently unused positions in the list, the relative positions of meaningful metrics within each group being maintained in the list;

    building an array of said offset values accessed by the corresponding state;

    building an array distinguishing meaningful and non-meaningful entries in the original array of distance metrics;

    whereby a measure of match between an input utterance and a vocabulary word model is obtainable by combining corresponding metrics using a default value for non-meaningful metrics and locating respective meaningful metrics in said combined list using said array of offset values.

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