Automatically retraining a speech recognition system
First Claim
1. A method for automatically updating a statistical model for a speech recognition system comprising:
- accepting data representing a plurality of individual prior speech utterances on which the statistical model is based;
accepting data representing one or more individual new speech utterances; and
generating an updated statistical model for use by the speech recognition system to recognize speech utterances, including relatively weighting the data representing the plurality of individual prior speech utterances and the data representing the one or more individual new speech utterances according to a weighting factor.
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Accused Products
Abstract
A telephone-based interactive speech recognition system is retrained using variable weighting and incremental retraining. Variable weighting involves changing the relative influence of particular measurement data to be reflected in a statistical model. Statistical model data is determined based upon an initial set of measurement data determined from an initial set of speech utterances. When new statistical model data is to be generated to reflect new measurement data determined from new speech utterances, a weighting factor is applied to the new measurement data to generate weighted new measurement data. The new statistical model data is then determined based upon the initial set of measurement data and the weighted new measurement data. Incremental retraining involves generating new statistical model data using prior statistical model data to reduce the amount of prior measurement data that must be maintained and processed. When prior statistical model data needs to be updated to reflect characteristics and attributes of new speech utterances, statistical model data is generated for the new speech utterances. Then the prior statistical model data and the statistical model data for the new measurement data are processed to generate the new statistical model data.
32 Citations
32 Claims
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1. A method for automatically updating a statistical model for a speech recognition system comprising:
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accepting data representing a plurality of individual prior speech utterances on which the statistical model is based;
accepting data representing one or more individual new speech utterances; and
generating an updated statistical model for use by the speech recognition system to recognize speech utterances, including relatively weighting the data representing the plurality of individual prior speech utterances and the data representing the one or more individual new speech utterances according to a weighting factor. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13)
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14. A computer-readable medium carrying one or more sequences of one or more instructions for automatically retraining a telephone-based interactive speech recognition system, the one or more sequences of one or more instructions including instructions which, when executed by one or more processors, cause the one or more processors to perform steps comprising:
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selecting a portion of prior measurement data for a prior set of speech utterances based upon a set of measurement data selection criteria;
retrieving the portion of prior measurement data;
determining new measurement data for a new set of speech utterances;
applying a weighting factor to the new measurement data to generate weighted new measurement data; and
generating new statistical model data for use by the telephone-based interactive speech recognition system, including using the portion of prior measurement data and the weighted new measurement data. - View Dependent Claims (15, 16, 17, 18, 19, 20, 21, 22)
the one or more weighting criteria includes an amount of data contained in the portion of prior measurement data, and the step of determining the weighting factor based upon the one or more weighting criteria includes determining the weighting factor based upon an amount of data contained in the portion of prior measurement data. -
17. A computer-readable medium as recited in claim 15, wherein
the one or more weighting criteria includes a ratio of an amount of data contained in the portion of prior measurement data to an amount of data contained in the new measurement data, and the step of determining the weighting factor upon the one or more weighting criteria includes determining the weighting factor based upon a ratio of an amount of data contained in the portion of prior measurement data to an amount of data contained in the new measurement data. -
18. A computer-readable medium as recited in claim 17, wherein
the set of measurement data selection criteria includes a confidence that a particular utterance was correctly recognized, and the step of selecting a portion of prior measurement data for a prior set of speech utterances based upon the set of measurement data selection criteria includes selecting a portion of prior measurement data for a prior set of speech utterances based upon the confidence that the particular utterance was correctly recognized. -
19. A computer-readable medium as recited in claim 17, wherein
the set of measurement data selection criteria includes whether a recognition result of a particular utterance was confirmed by a user, and the step of selecting a portion of prior measurement data for a prior set of speech utterances based upon the set of measurement data selection criteria includes selecting a portion of prior measurement data for a prior set of speech utterances based upon whether a recognition result of a particular utterance was confirmed by a user. -
20. A computer-readable medium as recited in claim 15, wherein
the one or more weighting criteria includes the subject matter of the new set of speech utterances, the step of determining the weighting factor based upon the one or more weighting criteria includes determining the weighting factor based upon the subject matter of the new set of speech utterances. -
21. A method as recited in claim 14, wherein
the set of measurement data selection criteria includes a confidence that a particular utterance was correctly recognized, and the step of selecting a portion of prior measurement data for a prior set of speech utterances based upon the set of measurement data selection criteria includes selecting a portion of prior measurement data for a prior set of speech utterances based upon the confidence that the particular utterance was correctly recognized. -
22. A computer-readable medium as recited in claim 14, wherein
the set of measurement data selection criteria includes whether a recognition result of a particular utterance was confirmed by a user, and the step of selecting a portion of prior measurement data for a prior set of speech utterances based upon the set of measurement data selection criteria includes selecting a portion of prior measurement data for a prior set of speech utterances based upon whether a recognition result of a particular utterance was confirmed by a user.
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23. A telephone-based interactive speech recognition system comprising:
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a storage medium; and
a retraining mechanism communicatively coupled to the storage medium, wherein the retraining mechanism is configured to select a portion of prior measurement data for a prior set of speech utterances based upon a set of measurement data selection criteria, retrieve the portion of prior measurement data from the storage medium, determine new measurement data for a new set of speech utterances, apply a weighting factor to the new measurement data to generate weighted new measurement data, and generate new statistical model data for use by the telephone-based interactive speech recognition system, including using the portion of prior measurement data and the weighted new measurement data. - View Dependent Claims (24, 25, 26, 27, 28, 29)
the one or more weighting criteria includes an amount of data contained in the portion of prior measurement data, and the retraining mechanism is further configured to determine the weighting factor based upon the one or more weighting criteria includes determining the weighting factor based upon an amount of data contained in the portion of prior measurement data. -
26. A telephone-based interactive speech recognition system as recited in claim 24, wherein
the one or more weighting criteria includes a ratio of an amount of data contained in the portion of prior measurement data to an amount of data contained in the new measurement data, and the step of determining the weighting factor based upon the one or more weighting criteria includes determining the weighting factor based upon a ratio of an amount of data contained in the portion of prior measurement data to an amount of data contained in the new measurement data. -
27. A telephone-based interactive speech recognition system as recited in claim 24, wherein
the one or weighting criteria includes the subject matter of the new set of speech the step of determining the weighting factor based upon the one or more weighting criteria includes determining the weighting factor based upon the subject matter of the new set of speech utterances. -
28. A telephone-based interactive speech recognition system as recited in claim 23, wherein
the set of measurement data selection criteria includes a confidence that a particular utterance was correctly recognized, and the step of selecting a portion of prior measurement data for a prior set of speech utterances based upon the set of measurement data selection criteria includes selecting a portion of prior measurement data for a prior set of speech utterances based upon the confidence that the particular utterance was correctly recognized. -
29. A telephone-based interactive speech recognition system as recited in claim 23, wherein
the set to measurement data selection criteria includes whether a recognition result of a particular utterance was confirmed by a user, and the step of selecting a portion of prior measurement data for a prior set of speech utterances based upon the set of measurement data selection criteria includes selecting a portion of prior measurement data for a prior set of speech utterances based upon whether a recognition result of a particular utterance was confirmed by a user.
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30. A method for automatically updating a statistical model for a speech recognition system comprising:
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selecting a portion of prior measurement data for a prior set of speech utterances based upon a set of measurement data selection criteria;
retrieving the portion of prior measurement data;
determining new measurement data for a new set of speech utterances;
applying a weighting factor to the new measurement data to generate weighted new measurement data;
generating new statistical model data using the portion of prior measurement data and the weighted new measurement data; and
using the new statistical model data to recognize speech utterances. - View Dependent Claims (31, 32)
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Specification