AUTOMATIC INPUT SIGNAL RECOGNITION USING LOCATION BASED LANGUAGE MODELING
First Claim
1. A computer implemented method for input signal recognition, the method comprising:
- receiving an input signal and a location associated with the input signal;
selecting a first language model from a plurality of local language models based on the location;
merging, via a processor, the first local language model and a global language model to generate a hybrid language model; and
recognizing the input signal based on the hybrid language model by identifying a word sequence that is statistically most likely to correspond to the input signal.
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Abstract
Input signal recognition, such as speech recognition, can be improved by incorporating location-based information. Such information can be incorporated by creating one or more language models that each include data specific to a pre-defined geographic location, such as local street names, business names, landmarks, etc. Using the location associated with the input signal, one or more local language models can be selected. Each of the local language models can be assigned a weight representative of the location'"'"'s proximity to a pre-defined centroid associated with the local language model. The one or more local language models can then be merged with a global language model to generate a hybrid language model for use in the recognition process.
47 Citations
25 Claims
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1. A computer implemented method for input signal recognition, the method comprising:
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receiving an input signal and a location associated with the input signal; selecting a first language model from a plurality of local language models based on the location; merging, via a processor, the first local language model and a global language model to generate a hybrid language model; and recognizing the input signal based on the hybrid language model by identifying a word sequence that is statistically most likely to correspond to the input signal. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11)
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12. A system for input signal recognition comprising:
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a server; receiving at the server, an input signal and a location associated with the input signal; generating a hybrid language model by incorporating a first local language model into a global language model, the first local language model corresponding to the location; and selecting a word sequence using the hybrid language model, wherein the word sequence has the greatest probability of corresponding to the input signal. - View Dependent Claims (13, 14, 15, 16, 17, 18)
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19. A non-transitory computer-readable storage medium storing instructions which, when executed by a computing device, cause the computing device to recognize an input signal, the instructions comprising:
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receiving an input signal and a location associated with the input signal; obtaining a first local language model and a global language model, the first local language model based on a location; generating a hybrid language model by merging the first local language model and the global language model; and recognizing the input signal by identifying a set of potential word sequences for the input signal, each word sequence having an associated probability of occurrence, and selecting the word sequence with the highest probability. - View Dependent Claims (20, 21, 22, 23, 24, 25)
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Specification