Toyota Infotechnology Center Co. Ltd.

Ianywhere Solutions, Inc.

John R Brookes

Norikazu Endo

Benjamin K Reaves

Babak Hodjat

Ramon Eduardo Prieto

Masahiko Funaki

A speech recognition method and system for use in a vehicle navigation system utilize grammar weighted based upon geographical information regarding the locations corresponding to the tokens in the grammars and/or the location of the vehicle for which the vehicle navigation system is used, in order to enhance the performance of speech recognition. The geographical information includes the distances between the vehicle location and the locations corresponding to the tokens, as well as the size, population, and popularity of the locations corresponding to the tokens.

Method and system for speech recognition using grammar weighted based upon location information

A speech recognition system recognizes an input speech signal by using a first speech recognizer and a second speech recognizer each coupled to a decision module. Each of the first and second speech recognizers outputs first and second recognized speech texts and first and second associated confidence scores, respectively, and the decision module selects either the first or the second speech text depending upon which of the first or second confidence score is higher. The decision module may also adjust the first and second confidence scores to generate first and second adjusted confidence scores, respectively, and select either the first or second speech text depending upon which of the first or second adjusted confidence scores is higher. The first and second confidence scores may be adjusted based upon the location of a speaker, the identity or accent of the speaker, the context of the speech, and the like.

Speech recognition system having multiple speech recognizers

A multiple pass speech recognition method includes a first pass and a second pass. The first pass recognizes an input speech signal to generate a first pass result. The second pass generates a first grammar having a portion set to match a first part of the input speech signal, based upon the context of the first pass result, and generate a second pass result. The method may further include a third pass grammar limiting the second part of the input speech signal to the second pass result. The third pass grammar includes a model corresponding to the first part of the input speech signal and varying within the second pass result. The third pass compares the first part of the input speech signal to the model while limiting the second part of the input speech signal to the second pass result.

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Oakland, CA, United States of America

John R Brookes