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Background learning of speaker voices

  • US 7,171,360 B2
  • Filed: 05/07/2002
  • Issued: 01/30/2007
  • Est. Priority Date: 05/10/2001
  • Status: Active Grant
First Claim
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1. A method of automatically identifying a speaker;

  • the method including;

    identifying a speaker by;

    receiving a test utterance from the speaker;

    determining a most likely one of a plurality of speaker models for the test utterance; and

    identifying the speaker associated with the most likely speaker model as the speaker of the test utterance;

    wherein the method includes generating the plurality of speaker models in the background by;

    receiving training utterances from a pool of utterances from the plurality of speakers in the background, without prior knowledge of the speakers who spoke the respective training utterances;

    blind clustering of the training utterances from the pool of utterances based on a predetermined criterion, wherein the blind clustering includes calculating a likelihood vector for each training utterance; and

    non-explicitly training for each of the clusters a corresponding speaker model, each of the models representing a speaker.

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