Itt Corporation

Itt Defense, Inc.

Itt Manufacturing Enterprises, Inc.

Itt Defense Communications

Alan L Higgins

Lawrence G Bahler

Robert E Wohlford

William Y Huang

Edwin H Wrench

Jack E Porter

Steven F Boll

A speech verification process involves comparison of enrollment and test speech data and an improved method of comparing the data is disclosed, wherein segmented frames of speech are analyzed jointly, rather than independently. The enrollment and test speech are both subjected to a feature extraction process to derive fixed-length feature vectors, and the feature vectors are compared, using a linear discriminant analysis and having no dependence upon the order of the words spoken or the speaking rate. The discriminant analysis is made possible, despite a relatively high dimensionality of the feature vectors, by a mathematical procedure provided for finding an eigenvector to simultaneously diagonalize the between-speaker and between-channel covariances of the enrollment and test data.

Method for speech processing involving whole-utterance modeling

An automated system obtains a confirmation of receipt of a notification by the intended recipient by having the recipient speak all or part of the notification. The words spoken by the recipient are determined by a computerized system using an automatic speech recognition algorithm. The computerized system determines whether the words spoken are those of the notification, and if they are, the system accepts the confirmation from the recipient. Optionally, the system additionally applies an automatic speaker recognition algorithm to determine whether the person reciting the notification has similar voice characteristics to the intended recipient based on a previous enrollment of the intended recipient's voice. The system can also record the recipient reciting the notification so that it can later be compared to the intended recipient's voice if the intended recipient repudiates the confirmation.

Automatic confirmation of personal notifications

A system and a method is disclosed for verifying a voice of a user conducting a telephone transaction. The system and method includes a mechanism for prompting the user to speak in a limited vocabulary. A feature extractor converts the limited vocabulary into a plurality of speech frames. A pre-processor is coupled to the feature extractor for processing the plurality of speech frames to produce a plurality of processed frames. The processing includes frame selection, which eliminates each of the plurality of speech frames having an absence of words. A Viterbi decoder is also coupled to said feature extractor for assigning a frame label to each of the plurality of speech frames to produce a plurality of frame labels. The processed frames and frame labels are then combined to produce a voice model, which includes each of the plurality of frame labels that correspond to the number of plurality of processed frames. A mechanism is also provided for comparing the voice model with the claimant's voice model, derived during a previous enrollment session. The voice model also is compared with an alternate voice model set, derived during previous enrollment sessions. The identity claimed is accepted if the voice model matches the claimant's voice model better than the alternative voice model set.

System for voice verification using matched frames

A method for performing noise suppression and channel equalization of a noisy voice signal comprising the steps of sampling the noisy voice signal at a predetermined sampling rate f,; segmenting the sampled voice signal into a plurality of frames having a predetermined number of samples per frame, over a predetermined temporal window; generating an N-point spectral sample representation of each of the sample signal frames; determining the magnitude of each of the N-point spectral samples and generating a histogram of the energy associated with each of the N-point spectral samples at a particular frequency; detecting a peak amplitude of the histogram which corresponds to a noise threshold N,associated with the particular frequency; determining a channel frequency response C,associated with the particular frequency by determining a geometric mean over all the spectral samples having magnitude exceeding the noise threshold N,; subtracting from each of the magnitudes of the N point spectral samples the noise threshold N,to provide a noise suppressed sample sequence; applying blind deconvolution to the noise suppressed samples; transforming the deconvolved noise suppressed sampled sequence to a temporal representation; shifting the temporal sample sequence in time by a predetermined amount; and adding the time shifted temporal samples over a period corresponding to the predetermined temporal window to provide a suppressed noise voice signal.

Noise suppression and channel equalization preprocessor for speech and speaker recognizers: method and apparatus

System for voice verification of telephone transactions

A telephone long distance service is provided using speaker verification to determine whether a user is a valid user or an impostor. The user claims an identity by offering some form of identification, typically by entering a calling card number on the phone's touch-tone keypad or by a magnetic strip on the card which is read by the telephone. Unrestricted, extemporaneous speech of a group of customers are digitized, analyzed in accordance with a PCM circuit, and characterized as a non-parametric set of speech feature vectors. The extemporaneous speech of the long distance telephone service user claiming the identity of a service customer via his card number is digitized and analyzed in a like manner. The identity of the user is verified by comparing, either during or after the call, the signals in accordance with an algorithm which compares a reference utterance of a known customer with input utterances from one or more unknown telephone service users, one of which users has claimed the identity of the customer. This comparison results in a decision to accept or reject the hypothesized identity. The identity hypothesis to be tested is thus derived from the calling card of the customer.

System and method for passive voice verification in a telephone network

A speaker verification system which accepts or rejects the claimed identity of an individual based on analysis and measurements of the speaker's utterances. The utterances are elicited by prompting the individual seeking identification to read test phrases chosen at random by the verification system composed of words from a small vocabulary. Nearest-neighbor distances between speech frames derived from such spoken test phrases and speech frames of corresponding vocabulary 'words' from previously stored utterances of the speaker seeking identification are computed along with distances between such spoken test phrases and corresponding vocabulary words for a set of reference speakers. The claim for identification is accepted or rejected based on the relationship among such distances and a predetermined threshold value.

Speaker verifier using nearest-neighbor distance measure

Similarity is measured between incoming speech and a plurality of candidate strings of filler and keyword templates to test the hypothesis of a keyword being present against the hypothesis of a keyword not being present in the input speech. As alternatives to a candidate string containing a keyword template, other candidate strings are assembled with filler templates of short speech sounds that may be similar to a keyword. A keyword is 'recognized' only when an optimal candidate string containing the corresponding keyword template is determined to match the input speech more closely than all other candidate strings. A concatenation penalty is added to the partial string score each time a new template is added to a candidate string, in order to bias the score in favor of a candidate string containing a longer, keyword template.

Keyword recognition system and method using template concantenation model

A real-time speech processing development system has a control subsystem (CS) and a recognition subsystem (RS) interconnected by a CS/RS interface. The control subsystem includes a control processor, an operator interface, a user interface, and a control program module for loading any one of a plurality of control programs which employ speech recognition processes. The recognition system RS includes a master processor, speech signal processor, and template matching processors all interconnected on a common bus which communicates with the control subsystem through the mediation of the CS/RS interface. The two-part configuration allows the control subsystem to be accessed by the operator for non-real-time system functions, and the recognition subsystem to be accessed by the user for real-time speech processing functions. An embodiment of a speaker verification system includes template enrollment, template training, recognition by template-concatenation and time alignment, silence and filler template generation, and speaker monitoring modes.

Real-time speech processing development system

An automatic speech recognition system employs parallel syntaxes with a first syntax operative to compare keyword templates with incoming speech over a given time interval and with a second syntax in parallel with the first and operative to compare filler templates with incoming speech over the same interval. Based on the best comparisons in each syntax a likelihood probability ratio is computed and compared against a selected threshold for determining whether the speech contains a valid phrase or keyword as compared to an undesirable utterance.

Method and apparatus of rejecting false hypotheses in automatic speech

The invention provides a method and system for speaker enrollment, as well as for speaker recognition. Speaker enrollment creates for each candidate speaker a set of short acoustic segments, or templates, of phonemic duration. An equal number of templates is derived from every candidate speaker's training utterance. A speaker's template set serves as a model for that speaker. Recognition is accomplished by employing a continuous speech recognition (CSR) system to match the recognition utterance with each speaker's template set in turn. The system selects the speaker whose templates match the recognition utterance most closely, that is, the speaker whose CSR match score is lowest. The method of the invention incorporates the entire training utterance in each speaker model, and explains the entire test utterance. The method of the invention models individual short segments of the speech utterances as well as their long-term statistics. Both static and dynamic speaker characteristics are captured in the speaker models.

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San Diego, CA, United States of America

Alan L Higgins