International Business Machines Corporation

Nuance Communications, Inc.

Jason William Pelecanos

Ganesh Nachiappa Ramaswamy

Jiri Navratil

Ran D Zilca

David Nahamoo

Hagai Aronowitz

Kenneth W Church

Orith Toledo-Ronen

Weizhong Zhu

Ron Hoory

Amir Geva

Ryan L Osborn

James H Nealand

Aaron K Baughman

Tomasz J Nowicki

Upendra V Chaudhari

Martin Franz

Shay Ben-David

Grzegorz Michal Swirszcz

Dimitrios B Dimitriadis

Jeffrey Scott McCarley

Nicholas Stephen Kersting

Petr Fousek

Josef Vopicka

Sarah C McAllister

Douglas George Heintzman

Janice J Kim

A diarization embodiment may include a system that clusters data up to a current point in time and consolidates it with the past decisions, and then returns the result that minimizes the difference with past decisions. The consolidation may be achieved by performing a permutation of the different possible labels and comparing the distance. For speaker diarization, a distance may be determined based on a minimum edit or hamming distance. The distance may alternatively be a measure other than the minimum edit or hamming distance. The clustering may have a finite time window over which the analysis is performed.

Prefix methods for diarization in streaming mode

A method comprising using at least one hardware processor for: providing a set of development supervectors representing features of biometric samples of multiple subjects, the biometric samples being of at least a first and a second different biometric modalities; providing at least a first and a second enrollment supervectors representing features of at least a first and a second enrollment biometric samples of a target subject correspondingly, wherein the at least first and second enrollment samples are of the at least first and the second different biometric modalities correspondingly; providing at least a first and a second verification supervectors representing features of at least a first and a second verification biometric samples of the target subject correspondingly, wherein the at least first and second verification samples are of the at least first and second different biometric modalities correspondingly; concatenating the development supervectors to a set of development generic supervector, the at least first and second enrollment supervectors to a single enrollment generic supervector and the at least first and second verification supervectors to a single verification generic supervector; and verifying an identity of the target subject based on a fused score calculated for the verification generic supervector, wherein the fused score is calculated based on the enrollment generic supervector and the set of development generic supervectors.

Biometric authentication

Embodiments of the present invention provide a computer-implemented method for communicating a reference code for a transaction. The method monitors a communication session conducted between a user and an agent via a communication channel, extracts user and channel properties from the monitored communication session, selects a reference code from a set of references codes stored on a database, in which the selection is based at least in part on the extracted communication channel properties and the extracted user properties, and then communicates the selected reference code to the user.

Adaptive selection of message data properties for improving communication throughput and reliability

Embodiments of the invention include method, systems and computer program products for role modeling. Aspects of the invention include receiving, by a processor, audio data, wherein the audio data includes a plurality of audio conversation for one or more speakers. The one or more segments for each of the plurality of audio conversations are partitioned. A speaker is associated with each of the one or more segments. The one or more segments for each of the plurality of audio conversations are labeled with roles utilizing a speaker recognition engine. Speakers are clustered based at least in part on a number of times the speakers are present in an audio conversation.

Role modeling in call centers and work centers

Systems and methods for maintaining speaker recognition performance are provided. A method for maintaining speaker recognition performance, comprises training a plurality of models respectively corresponding to speaker recognition scores from a plurality of speakers over a plurality of sessions, and using the plurality of models to conclude whether a speaker seeking access to an environment is a non-ideal target speaker or a non-ideal non-target speaker. Using the plurality of models to conclude comprises calculating a first probability that the speaker seeking access is the non-ideal target speaker, calculating a second probability that the speaker seeking access is the non-ideal non-target speaker, and determining whether the first probability, the second probability or a sum of the first probability and the second probability is above a probability threshold.

Detection of target and non-target users using multi-session information

Methods and apparatus are provided for sequential authentication of a user that employ one or more error rates characterizing each security challenge. According to one aspect of the invention, a user is challenged with at least one knowledge challenge to obtain an intermediate authentication result; and the user challenges continue until a cumulative authentication result satisfies one or more criteria. The intermediate authentication result is based, for example, on one or more of false accept and false reject error probabilities for each knowledge challenge. A false accept error probability describes a probability of a different user answering the knowledge challenge correctly. A false reject error probability describes a probability of a genuine user not answering the knowledge challenge correctly. The false accept and false reject error probabilities can be adapted based on field data or known information about a given challenge.

Method and apparatus for sequential authentication using one or more error rates characterizing each security challenge

A signal representative of an unpredictable audio stimulus is provided to a putative live speaker within a putative live recording environment. A second signal purportedly emanating from the putative live speaker and/or the environment is received. This second signal is examined for influence of the unpredictable audio stimulus on the putative live speaker and/or the putative live recording environment. The examining includes at least one of audio feedback analysis, Lombard analysis, and evoked otoacoustic response analysis. Based on the examining, a determination is made as to whether the putative live speaker is an actual live speaker and/or whether the putative live recording environment is an actual live recording environment.

Speaker liveness detection

A method and apparatus for remote access to a target application is disclosed where a system administrator may establish telephonic contact with an interactive voice response system and obtain access to the target application by speech communication. The interactive response system may authenticate the system administrator by implementing various measures including biometric measures. Once access is granted, the interactive response system may broker a communication between the target application using text/data and the system administrator using natural language.

Method and apparatus for remote command, control and diagnostics of systems using conversational or audio interface

A method and apparatus detect and localize electric faults in electrical power grids and circuit. High impedance faults are detected by analyzing data from remote sensor units deployed over the network using the algorithms of speech and speaker analysis software. This is accomplished by converting the voltage and/or current waveform readouts from the sensors into a digital form which is then transmitted to a computer located either near the sensors or at an operations center. The digitized data is converted by a dedicated software or software/hardware interface to a format accepted by a reliable and stable software solution, such as speech or speaker recognition software. The speech or speaker recognition software must be 'trained' to recognize various signal patterns that either indicate or not the occurrence of a fault. The readout of the speech or speaker recognition software, if indicating a fault, is transmitted to a central processor and displayed to provide information on the most likely type of fault. Automatic or human decision is then implemented based on the generated information.

Application of speech and speaker recognition tools to fault detection in electrical circuits

The present invention provides a system and method for treating distortion propagated though a detection system. The system includes a compensation module that compensates for untreated distortions propagating through the detection compensation system, a user model pool that comprises of a plurality of model sets, and a model selector that selects at least one model set from plurality of model sets in the user model pool. The compensation is accomplished by continually producing scores distributed according to a prescribed distribution for the at least one model set and mitigating the adverse effects of the scores being distorted and lying off a pre-set operating point. The method for treating distortion propagated though a detection system includes receiving a signal from a remote device, and compensating the signal for untreated distortions. The compensation includes selecting at least one relevant model set from a plurality of model sets, producing scores distributed according to a pre-described distribution for the at least one model set, and mitigating the adverse effect of the scores being distorted by rejecting a signal if it lies off a preset operating point.

Continuous adaptation in detection systems via self-tuning from target population subsets

There is provided an apparatus for providing a Text Independent (TI) speaker recognition mode in a Text Dependent (TD) Hidden Markov Model (HMM) speaker recognition system and/or a Text Constrained (TC) HMM speaker recognition system. The apparatus includes a Gaussian Mixture Model (GMM) generator and a Gaussian weight normalizer. The GMM generator is for creating a GMM by pooling Gaussians from a plurality of HMM states. The Gaussian weight normalizer is for normalizing Gaussian weights with respect to the plurality of HMM states.

Method and apparatus for training a text independent speaker recognition system using speech data with text labels

A method, system and program storage device are provided for machine diagnostics, detection and profiling using pressure waves, the method including profiling known sources, acquiring pressure wave data, analyzing the acquired pressure wave data, and detecting if the analyzed pressure wave data matches a profiled known source; the system including a processor, a pressure wave transducer in signal communication with the processor, a pressure wave analysis unit in signal communication with the processor, and a source or threat detection unit in signal communication with the processor; and the program storage device including program steps for profiling known sources, acquiring pressure wave data, analyzing the acquired pressure wave data, and detecting if the analyzed pressure wave data matches a profiled known source.

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Ossining, NY, United States of America

Jason William Pelecanos