International Business Machines Corporation

At&t Intellectual Property I, L.p.

Nuance Communications, Inc.

Sameer Maskey

Dimitri Kanevsky

Tara N Sainath

Sasha P Caskey

Vittorio R Castelli

Bhuvana Ramabhadran

Sara H Basson

Yuqing Gao

Michiel A U Bacchiani

Bowen Zhou

Radu Florian

Richard William Sproat

Xiaoqiang Luo

Brian E Roark

Hema Raghavan

Computing system resources are controlled based on the behavioral attributes associated with users of the computing system. These behavioral attributes are monitored in real time and through a historical log, and behavioral attributes that fall outside pre-determined preferred behavioral parameters are detected. Access by the computing system user to computing system resources contained in a preferred and habitually accessed computing system resource set associated with the computing system user are adjusted in response to the detection of the behavioral attribute outside the pre-determined preferred behavioral parameters.

Controlled resources based on good behavior

Systems and methods for using biometrics to select music preference are provided. A system for using biometrics to select music preferences for a user in a vehicle, comprises a music selection module electrically coupled to at least one biometric sensor in the vehicle, wherein the at least one biometric sensor senses a characteristic of the user and outputs data for the sensed characteristic to the music selection module, and wherein the music selection module selects a music selection for the user based on the sensed characteristic data, and a controller module electrically coupled to the music selection module to control playing of the music selection, wherein the controller module receives an output including the music selection from the music selection module.

System and method for using biometrics to predict and select music preferences

Creating training data for a natural language processing system may comprise obtaining natural language input, the natural language input annotated with one or more important phrases; and generating training instances comprising a syntactic parse tree of nodes representing elements of the natural language input augmented with the annotated important phrases. In another aspect, a classifier may be trained based on the generated training instances. The classifier may be used to predict one or more potential important phrases in a query.

Deep analysis of natural language questions for question answering system

An embodiment of the invention directed to a method is associated with data content, comprising discrete data portions including first data and second data portions separated from each other in the data content. A copy operation is implemented on data portions so that at least some of the data portions are each copied to a buffer, which include the first and second data portions. A paste operation is carried out to present each of the copied data portions as an input for an output data selection task. Prespecified criteria is used in the output data selection task to select a number of the copied data portions to be selected data for a given purpose, the selected number of copied data portions being less than data portions presented by the paste operation, and the selected copied data portions including the first and second data portions.

Clipboard for processing received data content

Techniques for client side translation cache prediction are provided. The techniques include obtaining meta data associated with a request, applying a cache prediction model to the meta data to automatically predict one or more translations associated with the request, and storing the one or more translations in a client translation cache.

Translation cache prediction

Techniques for facilitating communication are provided. The techniques include using a machine-to-machine communication to facilitate communication between one or more human users of a communicator device and a compatible communicator device, wherein using the machine-to-machine communication to facilitate communication between one or more human users comprises initiating a machine-to-machine communication with a compatible communicator device if the device is within the geographic proximity, wherein the machine-to-machine communication incorporates one or more related items from a user profile of each device automatically extracted by the device initiating the machine-to-machine communication, and conducting the machine-to-machine communication in a manner in which the communication can be monitored by the one or more human users.

Virtual communication techniques

A sparse representation method of text classification is described. An input text document is represented as a document feature vector y. A category dictionary H provides possible examples [h; h; . . . ; h] of the document feature vector y. The input text document is classified using a sparse representation text classification algorithm that solves for y=H&#x3b2; where a sparseness condition is enforced on &#x3b2; to select a small number of examples from the dictionary H to describe the document feature vector y.

Sparse representations for text classification

Systems and methods relate to generating a language model for use in, for example, a spoken dialog system or some other application. The method comprises building a class-based language model, generating at least one sequence network and replacing class labels in the class-based language model with the at least one sequence network. In this manner, placeholders or tokens associated with classes can be inserted into the models at training time and word/phone networks can be built based on meta-data information at test time. Finally, the placeholder token can be replaced with the word/phone networks at run time to improve recognition of difficult words such as proper names.

System and method of using meta-data in speech processing

A computer-implemented method for creating a disfluency translation lattice includes providing a plurality of weighted finite state transducers including a translation model, a language model, and a phrase segmentation model as input, performing a cascaded composition of the weighted finite state transducers to create a disfluency translation lattice, and storing the disfluency translation lattice to a computer-readable media.

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New York, NY, United States of America

Sameer Maskey