Patents by Inventor Jasdeep Singh

Jasdeep Singh 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).

  • Cross-lingual regularization for multilingual generalization
    Patent number: 11829727
    Abstract: Approaches for cross-lingual regularization for multilingual generalization include a method for training a natural language processing (NLP) deep learning module. The method includes accessing a first dataset having a first training data entry, the first training data entry including one or more natural language input text strings in a first language; translating at least one of the one or more natural language input text strings of the first training data entry from the first language to a second language; creating a second training data entry by starting with the first training data entry and substituting the at least one of the natural language input text strings in the first language with the translation of the at least one of the natural language input text strings in the second language; adding the second training data entry to a second dataset; and training the deep learning module using the second dataset.
    Type: Grant
    Filed: April 23, 2021
    Date of Patent: November 28, 2023
    Assignee: salesforce.com, inc.
    Inventors: Jasdeep Singh, Nitish Shirish Keskar, Bryan McCann
  • CROSS-LINGUAL REGULARIZATION FOR MULTILINGUAL GENERALIZATION
    Publication number: 20210240943
    Abstract: Approaches for cross-lingual regularization for multilingual generalization include a method for training a natural language processing (NLP) deep learning module. The method includes accessing a first dataset having a first training data entry, the first training data entry including one or more natural language input text strings in a first language; translating at least one of the one or more natural language input text strings of the first training data entry from the first language to a second language; creating a second training data entry by starting with the first training data entry and substituting the at least one of the natural language input text strings in the first language with the translation of the at least one of the natural language input text strings in the second language; adding the second training data entry to a second dataset; and training the deep learning module using the second dataset.
    Type: Application
    Filed: April 23, 2021
    Publication date: August 5, 2021
    Inventors: Jasdeep SINGH, Nitish Shirish KESKAR, Bryan MCCANN
  • Cross-lingual regularization for multilingual generalization
    Patent number: 11003867
    Abstract: Approaches for cross-lingual regularization for multilingual generalization include a method for training a natural language processing (NLP) deep learning module. The method includes accessing a first dataset having a first training data entry, the first training data entry including one or more natural language input text strings in a first language; translating at least one of the one or more natural language input text strings of the first training data entry from the first language to a second language; creating a second training data entry by starting with the first training data entry and substituting the at least one of the natural language input text strings in the first language with the translation of the at least one of the natural language input text strings in the second language; adding the second training data entry to a second dataset; and training the deep learning module using the second dataset.
    Type: Grant
    Filed: April 30, 2019
    Date of Patent: May 11, 2021
    Assignee: salesforce.com, inc.
    Inventors: Jasdeep Singh, Nitish Shirish Keskar, Bryan McCann
  • Cross-Lingual Regularization for Multilingual Generalization
    Publication number: 20200285706
    Abstract: Approaches for cross-lingual regularization for multilingual generalization include a method for training a natural language processing (NLP) deep learning module. The method includes accessing a first dataset having a first training data entry, the first training data entry including one or more natural language input text strings in a first language; translating at least one of the one or more natural language input text strings of the first training data entry from the first language to a second language; creating a second training data entry by starting with the first training data entry and substituting the at least one of the natural language input text strings in the first language with the translation of the at least one of the natural language input text strings in the second language; adding the second training data entry to a second dataset; and training the deep learning module using the second dataset.
    Type: Application
    Filed: April 30, 2019
    Publication date: September 10, 2020
    Inventors: Jasdeep Singh, Nitish Shirish Keskar, Bryan McCann