Patents by Inventor Abderrahim AIT-AZZI

Abderrahim AIT-AZZI 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).

  • Generation of natural language text from structured data using a fusion model
    Patent number: 10997374
    Abstract: Generating natural language text from structured data using a fusion model is disclosed. Based on an input dictionary, a first sequence of vectors is generated by a first encoder and a second sequence of vectors is generated by a second encoder. The first and second sequences of vectors are provided to an attention function which generates a modified sequence of vectors. A decoder decodes the modified sequence of vectors to generate a plurality of ordered sequences corresponding to a target natural language sentence. A predetermined number of candidate sentences are determined based on the plurality of ordered sequences and are ranked to select a sentence as the target natural language sentence.
    Type: Grant
    Filed: March 22, 2019
    Date of Patent: May 4, 2021
    Assignee: FORTIA FINANCIAL SOLUTIONS
    Inventors: Houda Bouamor, Sira Ferradans, Guillaume Hubert, Abderrahim Ait-Azzi
  • GENERATION OF NATURAL LANGUAGE TEXT FROM STRUCTURED DATA USING A FUSION MODEL
    Publication number: 20200302023
    Abstract: Generating natural language text from structured data using a fusion model is disclosed. Based on an input dictionary, a first sequence of vectors is generated by a first encoder and a second sequence of vectors is generated by a second encoder. The first and second sequences of vectors are provided to an attention function which generates a modified sequence of vectors. A decoder decodes the modified sequence of vectors to generate a plurality of ordered sequences corresponding to a target natural language sentence. A predetermined number of candidate sentences are determined based on the plurality of ordered sequences and are ranked to select a sentence as the target natural language sentence.
    Type: Application
    Filed: March 22, 2019
    Publication date: September 24, 2020
    Inventors: Houda BOUAMOR, Sira FERRADANS, Guillaume HUBERT, Abderrahim AIT-AZZI