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DOMAIN ADAPTATION IN SPEECH RECOGNITION VIA TEACHER-STUDENT LEARNING

  • US 20190051290A1
  • Filed: 08/11/2017
  • Published: 02/14/2019
  • Est. Priority Date: 08/11/2017
  • Status: Active Grant
First Claim
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1. A system providing for adaption of speech recognition models for speech recognition in new domains, comprising:

  • a processor; and

    a memory storage device including instructions that when executed by the processor enable the system to;

    select a teacher model configured for speech recognition of utterances in a source domain;

    produce a student model based on the teacher model for speech recognition of utterances in a target domain;

    provide source domain utterances to the teacher model to produce teacher posteriors for the source domain utterances;

    provide, in parallel to providing the source domain utterances, target domain utterances to the student model to produce student posteriors for the target domain utterances;

    determine whether student posteriors converge with the teacher posteriors;

    in response to determining that the student posteriors and the teacher posteriors converge, finalize the student model for use in speech recognition in the target domain; and

    in response to determining that the that the student posteriors and the teacher posteriors do not converge, update parameters of the student model based on divergences in the student posteriors and the teacher posteriors.

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