The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Jan. 24, 2017

Filed:

May. 20, 2010
Applicants:

Marc Dymetman, Grenoble, FR;

Wilker Ferreira Aziz, São Paulo, BR;

Nicola Cancedda, Grenoble, FR;

Jean-marc Coursimault, Revel, FR;

Vassilina Nikoulina, Grenoble, FR;

Lucia Specia, Wolverhampton, GB;

Inventors:

Marc Dymetman, Grenoble, FR;

Wilker Ferreira Aziz, São Paulo, BR;

Nicola Cancedda, Grenoble, FR;

Jean-Marc Coursimault, Revel, FR;

Vassilina Nikoulina, Grenoble, FR;

Lucia Specia, Wolverhampton, GB;

Assignee:

XEROX CORPORATION, Norwalk, CT (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06F 17/28 (2006.01);
U.S. Cl.
CPC ...
G06F 17/2827 (2013.01); G06F 17/2818 (2013.01);
Abstract

A system and a method for phrase-based translation are disclosed. The method includes receiving source language text to be translated into target language text. One or more dynamic bi-phrases are generated, based on the source text and the application of one or more rules, which may be based on user descriptions. A dynamic feature value is associated with each of the dynamic bi-phrases. For a sentence of the source text, static bi-phrases are retrieved from a bi-phrase table, each of the static bi-phrases being associated with one or more values of static features. Any of the dynamic bi-phrases which each cover at least one word of the source text are also retrieved, which together form a set of active bi-phrases. Translation hypotheses are generated using active bi-phrases from the set and scored with a translation scoring model which takes into account the static and dynamic feature values of the bi-phrases used in the respective hypothesis. A translation, based on the hypothesis scores, is then output.


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