Shrikanth Narayanan - Santa Monica CA, US Panayiotis Georgiou - La Crescenta CA, US
Assignee:
University of Southern California - Los Angeles CA
International Classification:
G06F 17/28 G10L 21/00
US Classification:
704 2, 704277
Abstract:
A socially-cognizant translation system that takes social state between speaker and listener into account when making the translation. The translation may be more formal or less formal based on the social relationship between speaker and listener. Profanities in the source speech may be detected, and used to determine the social cognizance. Also, the source speech can be translated without the profanity in the target language, instead using the meaning of the profanity.
Spoken Translation System Using Meta Information Strings
Shrikanth Narayanan - Santa Monica CA, US Panayiotis Georgiou - La Crescenta CA, US Murtaza Bulut - Los Angeles CA, US Dagen Wang - Yorktown Heights NY, US
Assignee:
University of Southern California - Los Angeles CA
International Classification:
G06F 17/28 G06F 17/20 G06F 17/27
US Classification:
704 2, 704 8, 704 9
Abstract:
Spoken translation system which detects both speech from the information and also detects meta information streams from the information. A first aspect produces an enriched training corpus of information for use in the machine translation. A second aspect uses two different extraction techniques, and combines them by lattice rescoring.
Shrikanth Narayanan - Santa Monica CA, US Panayiotis Georgiou - La Crescenta CA, US
Assignee:
UNIVERSITY OF SOUTHERN CALIFORNIA - Los Angeles CA
International Classification:
G09B 19/06
US Classification:
434157000
Abstract:
An application (computer program, an embodiment can be a game) which requires translation as one of its metrics is used to help the user can learn a language while operating the system (in a game embodiment, playing the game). The interaction is carried out only in a foreign language, but the application also includes translation capability. A virtual buddy can be used to translate between the native language and the foreign language so that the user can translate information and eventually learn information about the language by the process of interacting with the system (in an embodiment playing the game).
Communication System Using Mixed Translating While In Multilingual Communication
Shrikanth Narayanan - Santa Monica CA, US Panayiotis Georgiou - La Crescenta CA, US
Assignee:
UNIVERSITY OF SOUTHERN CALIFORNIA - Los Angeles CA
International Classification:
G06F 17/28
US Classification:
704002000
Abstract:
A translation between a source language and a target language. The items are divided, with secondary source language items or named entities being identified. Those entities are translated in a different way. For example, they may be copied into the target language, or translated in a special way that is based on their meaning, e.g., into a term that has a more descriptive meaning in the target language.
Shrikanth Narayanan - Santa Monica CA, US Panayiotis Georgiou - La Crescenta CA, US
Assignee:
UNIVERSITY OF SOUTHERN CALIFORNIA - Los Angeles CA
International Classification:
G09B 19/06
US Classification:
434157
Abstract:
An application (computer program, an embodiment can be a game) which requires translation as one of its metrics is used to help the user can learn a language while operating the system (in a game embodiment, playing the game). The interaction is carried out only in a foreign language, but the application also includes translation capability. A virtual buddy can be used to translate between the native language and the foreign language so that the user can translate information and eventually learn information about the language by the process of interacting with the system (in an embodiment playing the game).
Topic Specific Language Models Built From Large Numbers Of Documents
Abhinav Sethy - Los Angeles CA, US Panayiotis Georgiou - La Crescenta CA, US Shrikanth Narayanan - Santa Monica CA, US
Assignee:
University of Southern California - Los Angeles CA
International Classification:
G06F 7/00 G06F 17/28 G06F 17/30 G10L 15/00
US Classification:
707737, 704 4, 704231, 707748
Abstract:
Forming and/or improving a language model based on data from a large collection of documents, such as web data. The collection of documents is queried using queries that are formed from the language model. The language model is subsequently improved using the information thus obtained. The improvement is used to improve the query. As data is received from the collection of documents, it is compared to a rejection model, that models what rejected documents typically look like. Any document that meets the test is then rejected. The documents that remain are characterized to determine whether they add information to the language model, whether they are relevant, and whether they should be independently rejected. Rejected documents are used to update the rejection model; accepted documents are used to update the language model. Each iteration improves the language model, and the documents may be analyzed again using the improved language model.
University of Southern California since Feb 2003
Research Assistant Professor
Education:
University of Southern California 1999 - 2002
PhD, Engineering
University of Southern California 1996 - 1998
MSc, Engineering
University of Cambridge 1992 - 1996
MEng, Engineering
University of Cambridge 1992 - 1996
BA, Engineering
Skills:
Signal Processing Pattern Recognition Machine Learning Computer Vision Matlab Image Processing Algorithms Latex Mathematical Modeling Artificial Intelligence Digital Signal Processors C++ Simulations Natural Language Processing C Computer Science Statistics Mathematica Speech Recognition Behavioral Signal Processing Data Mining Scientific Computing Statistical Modeling Applied Mathematics R Speech Translation Speech Digital Signal Processing Opencv Numerical Analysis Simulink Digital Image Processing Text Mining Neural Networks Video Processing Python Research Programming Linux Teaching Data Analysis University Teaching Deep Learning Higher Education Science