International Business Machines Corporation

Nuance Communications, Inc.

Ganesh Nachiappa Ramaswamy

Jiri Navratil

Upendra V Chaudhari

Jan Kleindienst

Ran D Zilca

Daniel Mark Coffman

Ponani S Gopalakrishnan

Jason William Pelecanos

Stephane Herman Maes

Popani Gopalakrishnan

Chalapathy Venkata Neti

Anand Narasimhan

Ryan L Osborn

James H Nealand

Oleg Alecksandrovich

David Nahamoo

Genady Grabarnik

Olivier Verscheure

Harry William Printz

Alexander Faisman

Jan Sedivy

Apostol Ivanov Natsev

Juan Manuel Huerta

Gerasimos Potamianos

Giridharan R Iyengar

Imed Zitouni

Mohamed Kamal Omar

Douglas George Heintzman

Jagon Pelecanos

Janice J Kim

Kyle A Jamieson

Joseph Morris

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

An authentication framework is provided which enables dynamic user authentication that combines multiple authentication objects using a shared context and that permits customizable interaction design to suit varying user preferences and transaction/application requirements. For example, an automated technique for user authentication comprises the following steps/operations. First, user input is obtained. At least a portion of the user input is associated with two or more verification objects. Then, the user is verified based on the two or more verification objects in accordance with at least one verification policy operating on a context shared across the two or more verification objects. The user authentication technique of the invention may preferably be implemented in a flexible, distributed architecture comprising at least one client device coupled to at least one verification server. The client device and the verification server may operate together to perform the user authentication techniques of the invention.

Methods and apparatus for dynamic user authentication using customizable context-dependent interaction across multiple verification objects

An exemplary processor-implemented method of determining whether a user of an online communication resource is an undesirable user includes the steps of building at least one model based on at least one feature of a feature set using at least one machine learning technique; and classifying the user by comparing at least one feature of the feature set that is associated with the user to the at least one model, a determination as to whether the user is an undesirable user being based at least in part on the classification of the user.

Automatic detection of undesirable users of an online communication resource based on content analytics

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

An authentication framework is provided which enables dynamic user authentication that combines multiple authentication objects using a shared context and that permits customizable interaction design to suit varying user preferences and transaction/application requirements. Such a framework provides a high degree of flexibility, accuracy, convenience and robustness. In one illustrative aspect of the invention, an automated technique for user authentication comprises the following steps/operations. First, user input is obtained. At least a portion of the user input is associated with two or more verification objects. Then, the user is verified based on the two or more verification objects in accordance with at least one verification policy operating on a context shared across the two or more verification objects. The user authentication technique of the invention may preferably be implemented in a flexible, distributed architecture comprising at least one client device coupled to at least one verification server. The client device and the verification server may operate together to perform the user authentication techniques of the invention.

A method and system for speaker recognition and identification includes transforming features of a speaker utterance in a first condition state to match a second condition state and provide a transformed utterance. A discriminative criterion is used to generate a transform that maps an utterance to obtain a computed result. The discriminative criterion is maximized over a plurality of speakers to obtain a best transform for recognizing speech and/or identifying a speaker under the second condition state. Speech recognition and speaker identity may be determined by employing the best transform for decoding speech to reduce channel mismatch.

System and method for addressing channel mismatch through class specific transforms

A system, method and computer program product for performing blind change detection audio segmentation that combines hypothesized boundaries from several segmentation algorithms to achieve the final segmentation of the audio stream. Automatic segmentation of the audio streams according to the system and method of the invention may be used for many applications like speech recognition, speaker recognition, audio data mining, online audio indexing, and information retrieval systems, where the actual boundaries of the audio segments are required.

System and method using blind change detection for audio segmentation

A method and system for configuring available resources in real-time to automatically accommodate the needs of the system user in multi-modal distributed computing system is disclosed. Information about the location or environment of a wireless device is used, preferably in combination with user personal preferences and past history to modify the behavior of the wireless device, including the selection of the most appropriate mode of interaction with the device and the activation of applications thereon as appropriate.

Resource configuration in multi-modal distributed computing systems

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

In detection systems, such as speaker verification systems, for a given operating point range, with an associated detection 'cost', the detection cost is preferably reduced by essentially trading off the system error in the area of interest with areas essentially 'outside' that interest. Among the advantages achieved thereby are higher optimization gain and better generalization. From a measurable Detection Error Tradeoff (DET) curve of the given detection system, a criterion is preferably derived, such that its minimization provably leads to detection cost reduction in the area of interest. The criterion allows for selective access to the slope and offset of the DET curve (a line in case of normally distributed detection scores, a curve approximated by mixture of Gaussians in case of other distributions). By modifying the slope of the DET curve, the behavior of the detection system is changed favorably with respect to the given area of interest.

Optimization of detection systems using a detection error tradeoff analysis criterion

A method is presented which reduces data flow and thereby increases processing capacity while preserving a high level of accuracy in a distributed speech processing environment for speaker detection. The method and system of the present invention includes filtering out data based on a target speaker specific subset of labels using data filters. The method preserves accuracy and passes only a fraction of the data by optimizing target specific performance measures. Therefore, a high level of speaker recognition accuracy is maintained while utilizing existing processing capabilities.

Target specific data filter to speed processing

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 of generating a positional representation of a document, including identifying each unique term in a document and positions in the document at which the unique term appears, and for the each unique term, storing positional information derived from the positions into a positional representation.

System and method for positional representation of content for efficient indexing, search, retrieval, and compression

An intelligent imaging system, includes an image generator that projects multiple angle views of a user, a plurality of cameras for capturing a plurality of images of the user, an image processing unit, a style advisor, and a control mechanism.

Intelligent mirror

A system and method for verifying user identity, in accordance with the present invention, includes a conversational system for receiving inputs from a user and transforming the inputs into formal commands. A behavior verifier is coupled to the conversational system for extracting features from the inputs. The features include behavior patterns of the user. The behavior verifier is adapted to compare the input behavior to a behavior model to determine if the user is authorized to interact with the system.

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Ossining, NY, United States of America

Ganesh Nachiappa Ramaswamy