Patents by Inventor Markos Mylonakis

Markos Mylonakis has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Multi-domain machine translation model adaptation
    Patent number: 9235567
    Abstract: A method adapted to multiple corpora includes training a statistical machine translation model which outputs a score for a candidate translation, in a target language, of a text string in a source language. The training includes learning a weight for each of a set of lexical coverage features that are aggregated in the statistical machine translation model. The lexical coverage features include a lexical coverage feature for each of a plurality of parallel corpora. Each of the lexical coverage features represents a relative number of words of the text string for which the respective parallel corpus contributed a biphrase to the candidate translation. The method may also include learning a weight for each of a plurality of language model features, the language model features comprising one language model feature for each of the domains.
    Type: Grant
    Filed: January 14, 2013
    Date of Patent: January 12, 2016
    Assignee: XEROX CORPORATION
    Inventors: Markos Mylonakis, Nicola Cancedda
  • MULTI-DOMAIN MACHINE TRANSLATION MODEL ADAPTATION
    Publication number: 20140200878
    Abstract: A method adapted to multiple corpora includes training a statistical machine translation model which outputs a score for a candidate translation, in a target language, of a text string in a source language. The training includes learning a weight for each of a set of lexical coverage features that are aggregated in the statistical machine translation model. The lexical coverage features include a lexical coverage feature for each of a plurality of parallel corpora. Each of the lexical coverage features represents a relative number of words of the text string for which the respective parallel corpus contributed a biphrase to the candidate translation. The method may also include learning a weight for each of a plurality of language model features, the language model features comprising one language model feature for each of the domains.
    Type: Application
    Filed: January 14, 2013
    Publication date: July 17, 2014
    Applicant: XEROX CORPORATION
    Inventors: Markos Mylonakis, Nicola Cancedda