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Language models using non-linguistic context

  • US 9,842,592 B2
  • Filed: 02/12/2014
  • Issued: 12/12/2017
  • Est. Priority Date: 02/12/2014
  • Status: Active Grant
First Claim
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1. A method performed by data processing apparatus, the method comprising:

  • receiving, by the data processing apparatus, context data indicating non-linguistic context for an utterance;

    generating, by the data processing apparatus and based on the context data, feature scores for one or more non-linguistic features, the generating comprising generating multiple location feature scores, each location feature score indicating whether a user is currently located at a location corresponding to the location feature score, wherein each of the multiple location feature scores corresponds to a different location;

    providing, by the data processing apparatus, the feature scores for the one or more non-linguistic features as input to a log-linear language model that has been trained to generate probability scores using feature scores for non-linguistic features, the providing comprising providing the multiple location feature scores to a log-linear language model that has been trained to generate probability scores in response to receiving multiple location feature scores corresponding to different locations;

    receiving, by the data processing apparatus, probability scores generated by the log-linear language model using the one or more feature scores for the non-linguistic features;

    determining, by the data processing apparatus, a transcription for the utterance using the probability scores generated by the log-linear language model; and

    providing, by the data processing apparatus, the transcription determined using the probability scores generated by the log-linear language model.

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