International Business Machines Corporation

Bolt Beranek and Newman Inc.

Salim Estephan Roukos

Robert T Ward

Jiri Navratil

Xiaoqiang Luo

Abraham P Ittycheriah

Mukund Padmanabhan

Raymond Lau

Nandakishore Kambhatla

Hongyan Jing

Ronald Rosenfeld

Dimitri Kanevsky

Vittorio R Castelli

Bhuvana Ramabhadran

David Nahamoo

Michael Alan Picheny

David M Lubensky

Lalit R Bahl

Mark Edward Epstein

Ellen Marie Eide

Radu Florian

Chalapathy Venkata Neti

Jan Sedivy

Martin Franz

Ruhi Sarikaya

Jeffrey Scott McCarley

Satyanarayana Dharanipragada

Stephen A Della Pietra

Marcos Antonio Bergamo

Kishore A Papineni

Jian Ni

Robert David Preuss

Herbert Gish

Patrick M Peterson

Alan G Derr

A W Huggins

Kishore Ananda Papineni

Joshua David Koppelman

David Eubensky

Patrick Mangan Peterson

Alan Gregory Derr

A processor may receive a text segment. The processor may analyze the text segment at a plurality of granularity levels wherein each of the plurality of granularity levels has a comparative selection value for identifying one or more objects of interest within the text segment. The processor may select an optimized granularity level with an optimum comparative selection value. The processor may identify the one or more objects of interest within the text segment. The processor may display the one or more objects of interest to a user.

Text classification using models with complementary granularity and accuracy

According to an aspect, a first word in a first language and a second word in a second language in a bilingual corpus are stemmed. A probability for aligning the first stem and the second stem and a distance metric between the normalized first stem and the normalized second stem are calculated. The first word and the second word are identified as a cognate pair when the probability and the distance metric meet a threshold criterion and stored as a cognate pair in a set of cognates. A candidate sentence in the second language is retrieved from a corpus. The candidate sentence is filtered by the active vocabulary of a user in the second language and the set of cognates. A sentence quality score is calculated for the candidate sentence; and the candidate sentence is ranked for presentation to the user based on the sentence quality scorer.

Automatic cognate detection in a computer-assisted language learning system

A method of identifying and using side information available to statistical machine translation systems within an enterprise setting, the method including extracting user-specific interaction and non-interaction-based information from at least one corresponding database within the enterprise for each of a plurality of users, aggregating the user-specific interaction and non-interaction based information from a plurality of users, by using a processor on a computer, to tune and adapt background translation and language models, and updating all relevant models within the enterprise after user activity based on the tuned and adapted translation and language models.

Machine translation with side information

A Bell Tree data structure is provided to model the process of chaining the mentions, from one or more documents, into entities, tracking the entire process; where the data structure is used in an entity tracking process that produces multiple results ranked by a product of probability scores.

Mention-synchronous entity tracking: system and method for chaining mentions

Mention-synchronous entity tracking system and method for chaining mentions

An arrangement for adapting statistical parsers to new data using a mathematical transform, particularly a Markov transform. In particular, it is assumed that an initial statistical parser is available and a batch of new data is given. The initial model is mapped to a new model by a Markov matrix, each of whose rows sums to one. In the unsupervised setup, where 'true' parses are missing, the transform matrix is obtained by maximizing the log likelihood of the parses of test data decoded using the model before adaptation. The proposed algorithm can be applied to supervised adaptation, as well.

Adaptation of statistical parsers based on mathematical transform

A method for recognizing speech includes the steps of providing a generic model having a baseform representation of a vocabulary of words, identifying a subset of words relating to an application, constructing a task specific model for the subset of words, constructing a composite model by combining the generic and task specific models and modifying the baseform representation of the subset of words such that the subset of words are recognized by the task specific model. A system for recognizing speech includes a composite model having a generic model having a generic baseform representation of a vocabulary of words and a task specific model for recognizing a subset of words relating to an application wherein the subset of words are recognized using a modified baseform representation. A recognizer compares words input thereto with the generic model for words other than the subset of words and with the task specific model for the subset of words.

Specific task composite acoustic models

A system for conversant interaction includes a recognizer for receiving and processing input information and outputting a recognized representation of the input information. A dialog manager is coupled to the recognizer for receiving the recognized representation of the input information, the dialog manager having task-oriented forms for associating user input information therewith, the dialog manager being capable of selecting an applicable form from the task-oriented forms responsive to the input information by scoring the forms relative to each other. A synthesizer is employed for converting a response generated by the dialog manager to output the response. A program storage device and method are also provided.

Natural language task-oriented dialog manager and method

A messaging system for receiving speech over a telephone and converting the speech to text includes a first server for receiving speech input by a user, a speech recognition system for converting the speech to text, a speech synthesizer for converting the text to speech for playing back the synthesized speech for correction by the user and a correction mechanism for enabling the user to correct the speech such that the corrected speech is provided as text for transmittal over a communication system.

Telephone messaging and editing system

A system and method for translating a series of source words in a first language to a series of target words in a second language is provided. The system includes an input device for inputting the series of source words. A fertility hypothesis generator operatively coupled to the input device generates at least one fertility hypotheses for a fertility of a source word, based on the source word and a context of the source word. A sense hypothesis generator operatively coupled to the input device generates sense hypotheses for a translation of the source word, based on the source word and the context of the source word. A fertility model operatively coupled to the fertility hypothesis generator determines a probability of the fertility of the source word, based on the source word and the context of the source word. A sense model operatively coupled to the sense hypothesis generator determines a probability of a target word being a correct translation of the source word, based on the source word and the context of the source word. A decoder operatively coupled to the fertility and sense models for generating a list of target words for the translation of the source word, based on the probability calculated by the fertility model and the probability calculated by the sense model.

Statistical translation system and method for fast sense disambiguation

A fast vocabulary independent method for spotting words in speech utilizes a preprocessing step and a coarse-to-detailed search strategy for spotting a word/phone sequence in speech. The preprocessing includes a Viterbi-beam phone level decoding using a tree-based phone language model. The coarse search matches phone-ngrams to identify regions of speech as putative word hits, and the detailed search performs an acoustic match at the putative hits with a model of the given word included in the vocabulary of the recognizer.

Fast vocabulary independent method and apparatus for spotting words in

A system for translating a first word set in a source language into a second word set in a target language, the system comprising: input means for inputting the first word set into the system; tagging means for tagging the first word set input to the system so as to at least substantially reduce non-essential variability in the first word set; translation means including a single a posteriori conditional probability model and a target candidate store for storing target language candidate word sets, wherein the translation means employs the single model to evaluate the target language candidate word sets in order to select the target language candidate word set having a best score with respect to the first word set; and output means for outputting the best scoring target language candidate word set as the second word set in the target language.

Statistical translation system with features based on phrases or groups

The invention proposes using statistical methods to do natural language understanding. The key notion is that there are 'strings' of words in the natural language, that correspond to a single semantic concept. One can then define an alignment between an entire semantic meaning (consisting of a set of semantic concepts), and the English. This is modeled using P(E,A.vertline.S). One can model p(S) separately. This allows each parameter to be modeled using many different statistical models.

Statistical natural language understanding using hidden clumpings

A method of gender dependent speech recognition includes the steps of identifying phone state models common to both genders, identifying gender specific phone state models, identifying a gender of a speaker and recognizing acoustic data from the speaker. A method of constructing a gender-dependent speech recognition model includes the steps of providing training data of a known gender, aligning the training data, tagging the training data with a gender to create gender-tagged data, determining a gender question at a node to determine gender dependence of the gender-tagged data, determining a phonetic context question at the node to determine phonetic context dependence of the gender-tagged data, determining a highest value of an evaluation function between the gender dependence and the phonetic context dependence to determine which dependence is a dominant dependence, splitting the data of the dominant dependence into child nodes according to likelihood criteria, comparing the highest value with a threshold value to determine if additional splitting is necessary, repeating theses steps for each child node until the highest value is below the threshold value and counting the nodes having gender dependence to determine an overall gender dependence level. A gender-dependent speech recognition system includes an input device for inputting speech to a preprocessor. The preprocessor converts the speech into acoustic data, and a processor for identifies gender-dependent phone state models and phone state modes common to both genders. The phone state models are stored in a memory device wherein the processor recognizes the speech in accordance with the phone state models.

Speech recognition models combining gender-dependent and

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Scarsdale, NY, United States of America

Salim Estephan Roukos