公开(公告)号：US11003867B2

公开(公告)日：2021-05-11

申请号：US16399429

申请日：2019-04-30

Applicant: salesforce.com, inc.

Inventor： Jasdeep Singh ,  Nitish Shirish Keskar ,  Bryan McCann

IPC: G06F40/00 ,  G06F40/58 ,  G06N20/00 ,  G06N3/08 ,  G06F40/51

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.

公开(公告)号：US11829727B2

公开(公告)日：2023-11-28

申请号：US17239297

申请日：2021-04-23

Applicant: salesforce.com, inc.

Inventor： Jasdeep Singh ,  Nitish Shirish Keskar ,  Bryan McCann

IPC: G06F40/00 ,  G06F40/58 ,  G06N20/00 ,  G06N3/08 ,  G06F40/51

CPC classification number: G06F40/58 ,  G06F40/51 ,  G06N3/08 ,  G06N20/00

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.

公开(公告)号：US20200285706A1

公开(公告)日：2020-09-10

申请号：US16399429

申请日：2019-04-30

Applicant: salesforce.com, inc.

Inventor： Jasdeep Singh ,  Nitish Shirish Keskar ,  Bryan McCann

IPC: G06F17/28 ,  G06N3/08 ,  G06N20/00

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.