At+t Corp.

Piyush C Modi

Randy Glen Goldberg

Richard R Rosinski

Deborah W Brown

Mazin G Rahim

Richard M Sachs

A method and apparatus for reducing a set of reference identifiers to a candidate subset of reference identifiers. The reference identifiers are associated in memory with a plurality of index codes. A user provides an input identifier, causing a recognizing device of the present invention to produce a recognized identifier on the basis of the input identifier. The present invention determines an index code based on the recognized identifier and on the basis of a plurality of pre-stored confusion sets of characters that group together in individual confusion sets those characters having a relatively high likelihood of being confused with each other by the recognizing device. After matching the determined index code with one of the reference index codes, the present invention determines which reference index codes are within a predetermined distance of the matched reference index code. The reference identifiers that are associated with these reference index codes constitute the candidate subset of reference identifiers.

Confusion set-base method and apparatus for pruning a predetermined arrangement of indexed identifiers

A multiple confidence measures subsystem of an automated speech recognition system allows otherwise independent confidence measures to be integrated and used for both training and testing on a consistent basis. Speech to be recognized is input to a speech recognizer and a recognition verifier of the multiple confidence measures subsystem. The speech recognizer generates one or more confidence measures. The speech recognizer preferably generates a misclassification error (MCE) distance as one of the confidence measures. The recognized speech output by the speech recognizer is input to the recognition verifier, which outputs one or more confidence measures. The recognition verifier preferably outputs a misverification error (MVE) distance as one of the confidence measures. The confidence measures output by the speech recognizer and the recognition verifier are normalized and then input to an integrator. The integrator integrates the various confidence measures during both a training phase for the hidden Markov models implemented in the speech recognizer and the recognition verifier and during testing of the input speech. The integrator is preferably implemented using a multi-layer perceptron (MLP). The output of the integrator, rather than the recognition verifier, determines whether the recognized utterance hypothesis generated by the speech recognizer should be accepted or rejected.

Method and apparatus for discriminative utterance verification using

A method and apparatus for recognizing an identifier entered by a user. A caller enters a predetermined identifier through a telephone handset. A signal representing the entered identifier is transmitted to a remote recognizer, which responds to the signal by producing a recognized output intended to match the entered identifier. The present invention compares this recognized identifier with a list of valid reference identifiers to determine which one of these reference identifiers most likely matches the entered identifier. In performing this determination, the present invention employs a confusion matrix, which is an arrangement of probabilities that indicate the likelihood that a given character in a particular character position of the reference identifier would be recognized by the recognizer as a character in the corresponding character position of the recognized identifier. This determination yields an identifier recognition probability for every reference identifier, and the present invention selects the reference identifier with the highest identifier recognition probability as most likely corresponding to the spoken identifier. The invention is also provided with the capability of improving the recognition accuracy of the confusion matrix by eliminating from consideration the most often confused characters.

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Flemington, NJ, United States of America

Piyush C Modi