Abstract: A speaker identification system is provided that constructs speaker models using a discriminant analysis technique where the data in each class is modeled by Gaussian mixtures. The speaker identification method and apparatus determines the identity of a speaker, as one of a small group, based on a sentence-length password utterance. A speaker's utterance is received and a sequence of a first set of feature vectors are computed based on the received utterance. The first set of feature vectors are then transformed into a second set of feature vectors using transformations specific to a particular segmentation unit, and likelihood scores of the second set of feature vectors are computed using speaker models trained using mixture discriminant analysis. The likelihood scores are then combined to determine an utterance score and the speaker's identity is validated based on the utterance score. The speaker identification method and apparatus also includes training and enrollment phases.

Abstract: A speaker identification system is provided that constructs speaker models using a discriminant analysis technique where the data in each class is modeled by Gaussian mixtures. The speaker identification method and apparatus determines the identity of a speaker, as one of a small group, based on a sentence-length password utterance. A speaker's utterance is received and a sequence of a first set of feature vectors are computed based on the received utterance. The first set of feature vectors are then transformed into a second set of feature vectors using transformations specific to a particular segmentation unit, and likelihood scores of the second set of feature vectors are computed using speaker models trained using mixture discriminant analysis. The likelihood scores are then combined to determine an utterance score and the speaker's identity is validated based on the utterance score. The speaker identification method and apparatus also includes training and enrollment phases.

Abstract: A signal processing arrangement uses a codebook of first vector quantized speech feature signals formed responsive to a large collection of speech feature signals. The codebook is altered by combining the first speech feature signals of the codebook with second speech feature signals generated responsive to later input speech patterns during normal speech processing. A speaker recognition template can be updated in this fashion to take account of change which may occur in the voice and speaking characteristics of a known speaker.

Abstract: An arrangement for endpoint detection improves speech recognition accuracy and lowers rejection rates by developing an ordered list of endpoint candidates. A triple thresholding technique defines energy signal pulses. The energy pulses are combined according to predetermined criteria to form the endpoint candidates.

Abstract: In a speaker recognition and verification arrangement, acoustic feature templates are stored for predetermined reference words. Each template is a standardized set of acoustic features for one word, formed for example by averaging the values of acoustic features from a plurality of speakers. Responsive to the utterances of identified speakers, a set of signals representative of the correspondence of the identified speaker's features with said feature templates of said reference words is generated. An utterance of an unknown speaker is analyzed and the reference word sequence of the utterance is identified. A set of signals representative of the correspondence of the unknown speaker's utterance features and the stored templates for the recognized words is generated. The unknown speaker is identified jointly responsive to the correspondence signals of the identified speakers and unknown speaker.

Abstract: A speech controlled dialing circuit identifies input utterances which may be a command word (mode select), repertory word (dialing name or number), or non-recognized ("Other"). Responsive to the identification of each occurring input utterance, a set of predetermined templates are selected to identify the next occuring utterance. A programmed microprocessor system is described to implement the main controller function.

Abstract: An arrangement for retrieving information from a directory responsive to a sequence of spoken character signals in which a set of probable characters for each character signal is stored in a position ordered array. A candidate word is formed from the most probable characters of the array and the directory is repeatedly searched for words therein which match a candidate word. After each unsuccessful search, the candidate word is modified by selectively substituting array characters for mismatched position characters on the basis of the closest mismatched word found in the preceding search. If there are no more array characters for substitution after an unsuccessful search, a new candidate word is formed by placing an ignore character in the first mismatched position of the best candidate word of all preceding searches. The position of the ignore mismatch character is shifted left each time no further array characters are available for substitution.

Abstract: A speech controlled dialing circuit identifies input utterances which may be a command word (mode select), repertory word (dialing name or number), or nonrecognized ("Other"). Responsive to the identification of each occurring input utterance, a set of predetermined templates are selected to identify the next occuring utterance. A programmed microprocessor system is described to implement the main controller function.

Abstract: An arrangement for endpoint detection improves speech recognition accuracy and lowers rejection rates by developing an ordered list of endpoint candidates. A triple thresholding technique defines energy signal pulses. The energy pulses are combined according to predetermined criteria to form the endpoint candidates.