International Business Machines Corporation

Nuance Communications, Inc.

Alcatel-lucent USA Inc.

Imed Zitouni

Vittorio R Castelli

Ganesh Nachiappa Ramaswamy

Ossama S Emam

Radu Florian

Girija Yegnanarayanan

Bing Hua Zhao

Martin Franz

Minkyu Lee

Nandakishore Kambhatla

Ruhi Sarikaya

Xiaoqiang Luo

John Ferdinand Pitrelli

Salim E Roukos

Brian William Delaney

Qiru Zhou

Neal Snider

Scott McCarley

Cascaded models may be applied to extract facts from a medical text. A first model may be applied to at least a portion of the medical text. The first model extracts at least one first medical fact. The at least one first medical fact is linked to at least first text in the at least a portion of the medical text. A second model may be applied to the first text. The second model extracts at least one second fact that is an attribute of the at least one first medical fact.

Methods and apparatus for extracting facts from a medical text

A method, an apparatus and an article of manufacture for determining a dropped pronoun from a source language. The method includes collecting parallel sentences from a source and a target language, creating at least one word alignment between the parallel sentences in the source and the target language, mapping at least one pronoun from the target language sentence onto the source language sentence, computing at least one feature from the mapping, wherein the at least one feature is extracted from both the source language and the at least one pronoun projected from the target language, and using the at least one feature to train a classifier to predict position and spelling of at least one pronoun in the target language when the at least one pronoun is dropped in the source language.

Predicting pronouns of dropped pronoun style languages for natural language translation

Systems and methods are provided for automated semantic role labeling for languages having complex morphology. In one aspect, a method for processing natural language text includes receiving as input a natural language text sentence comprising a sequence of white-space delimited words including inflicted words that are formed of morphemes including a stem and one or more affixes, identifying a target verb as a stem of an inflicted word in the text sentence, grouping morphemes from one or more inflicted words with the same syntactic role into constituents, and predicting a semantic role of a constituent for the target verb.

Systems and methods for automatic semantic role labeling of high morphological text for natural language processing applications

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 system and method for restoration of diacritics includes making classification decisions regarding an utterance in accordance with an aggregate of a plurality of information sources in a diacritization model for diacritic restoration. A best diacritic representation is determined for graphemes in the utterance based upon a best match with the diacritization model. A diacritically restored representation of the utterance is output.

System and method for diacritization of text

A method for performing packet loss concealment of lost packets in Voice over IP (Internet Protocol) speech transmission. Statistical n-gram models are initially created with use of a training speech corpus, and then, packets lost during transmission are advantageously replaced based on these models. In particular, the existence of statistical patterns in successive voice over IP (VoIP) packets is advantageously exploited by first using conventional vector quantization (VQ) techniques to quantize the parameter data for each packet with use of a corresponding VQ index, and then determining statistical correlations between consecutive sequences of such VQ indices representative of the corresponding sequences of n packets. The statistic n-gram predictive models so created are then used to predict parameter data for use in representing lost data packets.

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White Plains, NY, United States of America

Imed Zitouni