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:
Jun. 20, 2023

Filed:

Oct. 15, 2019
Applicant:

Naver Corporation, Seongnam-si, KR;

Inventors:

Vu Cong Duy Hoang, Brunswick West, AU;

Ioan Calapodescu, Grenoble, FR;

Marc Dymetman, Grenoble, FR;

Assignee:

NAVER CORPORATION, Seongnam-si, KR;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06N 3/08 (2023.01); G06F 17/18 (2006.01); G06F 40/30 (2020.01); G06N 3/04 (2023.01); G06F 40/58 (2020.01);
U.S. Cl.
CPC ...
G06N 3/08 (2013.01); G06F 17/18 (2013.01); G06F 40/30 (2020.01); G06F 40/58 (2020.01);
Abstract

Methods for training a neural sequence-to-sequence (seq2seq) model. A processor receives the model and training data comprising a plurality of training source sequences and corresponding training target sequences, and generates corresponding predicted target sequences. Model parameters are updated based on a comparison of predicted target sequences to training target sequences to reduce or minimize both a local loss in the predicted target sequences and an expected loss of one or more global or semantic features or constraints between the predicted target sequences and the training target sequences given the training source sequences. Expected loss is based on global or semantic features or constraints of general target sequences given general source sequences.


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