Language models using non-linguistic context
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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Abstract
Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for language models using non-linguistic context. In some implementations, context data indicating non-linguistic context for the utterance is received. Based on the context data, feature scores for one or more non-linguistic features are generated. The feature scores for the non-linguistic features are provided to a language model trained to process scores for non-linguistic features. The output from the language model is received, and a transcription for the utterance is determined using the output of the language model.
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Citations
17 Claims
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1. A method performed by data processing apparatus, the method comprising:
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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. - View Dependent Claims (2, 3, 4, 5, 6, 7, 14, 15, 16, 17)
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8. A system comprising:
one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising; receiving, by the one or more computers, context data indicating non-linguistic context for an utterance; generating, by the one or more computers 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 one or more computers, 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 one or more computers, probability scores generated by the log-linear language model using the one or more feature scores for the non-linguistic features; determining, by the one or more computers, a transcription for the utterance using the probability scores generated by the log-linear language model; and providing, by the one or more computers, the transcription determined using the probability scores generated by the log-linear language model. - View Dependent Claims (9, 10, 11)
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12. A non-transitory computer storage device encoded with a computer program, the program comprising instructions that when executed by one or more computers cause the one or more computers to perform operations comprising:
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receiving, by the one or more computers, context data indicating non-linguistic context for an utterance; generating, by the one or more computers 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 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 one or more computers, 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 one or more computers, probability scores generated by the log-linear language model using the one or more feature scores for the non-linguistic features; determining, by the one or more computers, a transcription for the utterance using the probability scores generated by the log-linear language model; and providing, by the one or more computers, the transcription determined using the probability scores generated by the log-linear language model. - View Dependent Claims (13)
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Specification