Method of evaluating an utterance in a speech recognition system
First Claim
1. A method of evaluating an utterance in a speech recognition system, said method comprising the steps of:
- receiving new training data in said speech recognition system;
calculating statistical parameters for said new training data;
calculating global statistical parameters based upon said statistical parameters for said new training data; and
updating a garbage model based upon said global statistical parameters.
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Abstract
The present invention provides a method of calculating, within the framework of a speaker dependent system, a standard filler, or garbage model, for the detection of out-of-vocabulary utterances. In particular, the method receives new training data in a speech recognition system (202); calculates statistical parameters for the new training data (204); calculates global statistical parameters based upon the statistical parameters for the new training data (206); and updates a garbage model based upon the global statistical parameters (208). This is carried out on-line while the user is enrolling the vocabulary. The garbage model described in this disclosure is preferably an average speaker model, representative of all the speech data enrolled by the user to date. Also, the garbage model is preferably obtained as a by-product of the vocabulary enrollment procedure and is similar in it characteristics and topology to all the other regular vocabulary HMMs.
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Citations
40 Claims
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1. A method of evaluating an utterance in a speech recognition system, said method comprising the steps of:
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receiving new training data in said speech recognition system;
calculating statistical parameters for said new training data;
calculating global statistical parameters based upon said statistical parameters for said new training data; and
updating a garbage model based upon said global statistical parameters. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19)
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20. A method of evaluating an utterance in a speaker-dependent speech recognition system for receiving data, said method comprising the steps of:
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receiving user provided training data;
calculating statistical parameters for said new training data;
calculating a global mean and global variance based upon said mean and said covariance for said new training data; and
updating a garbage model based upon said global mean and said global covariance. - View Dependent Claims (21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38)
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39. A method of evaluating an utterance in a speaker-dependent speech recognition system for receiving data, said method comprising the steps of:
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calculating a global mean and a global covariance based upon previously received training data;
receiving new training data;
calculating a mean and a covariance for said new training data;
updating said global mean and said global covariance based upon said mean and said covariance for said new training data; and
updating a garbage model based upon an updated global mean and an updated global covariance.
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40. A method of evaluating an utterance in a speaker-dependent speech recognition system for receiving data, said method comprising the steps of:
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calculating a global mean and a global covariance based upon previously received training data;
receiving new training data;
calculating a mean and a covariance for said new training data;
updating said global mean and said global covariance based upon said mean and said covariance for said new training data;
updating a single state HMM model for all data based upon an updated global mean and an updated global covariance;
receiving new data for operating said speaker-dependent speech recognition system;
comparing a model for said new data to a plurality of models previously stored in said speaker-dependent speech recognition system;
determining which of said plurality of models is a single state HMM model for all data;
multiplying said single state HMM model for all data by a penalty weight;
comparing said plurality of models as modified by said penalty weight to determine a best model from the list of active models; and
rejecting said utterance if a garbage model has been selected as the best model from the list of active models.
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Specification