Exemplar-based latent perceptual modeling for automatic speech recognition

  • US 8,935,167 B2
  • Filed: 09/25/2012
  • Issued: 01/13/2015
  • Est. Priority Date: 09/25/2012
  • Status: Active Grant
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First Claim
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1. A method for recognizing speech in an output domain, the method comprising:

  • at a device comprising one or more processors and memory;

    establishing a global speech recognition model based on an initial set of training data;

    receiving a plurality of input speech segments to be recognized in the output domain; and

    for each of the plurality of input speech segments;

    identifying in the global speech recognition model a respective set of focused training data relevant to the input speech segment;

    generating a respective focused speech recognition model based on the respective set of focused training data;

    and providing the respective focused speech recognition model to a recognition device for recognizing the input speech segment in the output domain;

    wherein establishing the global speech recognition model based on the initial set of training data further comprises;

    generating the initial set of training data from a plurality of training speech samples, the initial set of training data including an initial set of speech segments and an initial set of speech templates;

    and deriving a global latent space from the initial set of speech segments and the initial set of speech templates.

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