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Method and apparatus for training Hidden Markov Model

  • US 5,890,114 A
  • Filed: 02/28/1997
  • Issued: 03/30/1999
  • Est. Priority Date: 07/23/1996
  • Status: Expired due to Term
First Claim
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1. A training method for generating parameters of an HMM (hidden Markov model) for speech recognition, comprising:

  • converting speech to digital sound signals;

    producing training data from the digital sound signals;

    obtaining an initial estimated parameter of the HMM based on the training data;

    obtaining a set of centroid states, bydetermining a state of the HMM using the initial estimated parameter, andclustering the determined state of the HMM;

    reconstructing the HMM with the set of centroid states;

    obtaining a new estimated parameter of the reconstructed HMM; and

    repeatedly reexecutingthe obtaining a set of centroid states,the reconstructing the HMM, andthe obtaining a new estimated parameter,until a variation value of likelihood of the new estimated parameter becomes not more than a preset value, wherein the reexecution of the obtaining a set of centroid states uses a last obtained new estimated parameter in place of the initial estimated parameter.

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