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:
Oct. 22, 2024

Filed:

Nov. 10, 2021
Applicant:

Samsung Electronics Co., Ltd., Suwon-si, KR;

Inventors:

Jiyoun Hong, Suwon-si, KR;

Hyeonmok Ko, Suwon-si, KR;

Dayoung Kwon, Suwon-si, KR;

Jonggu Kim, Suwon-si, KR;

Seoha Song, Suwon-si, KR;

Kyenghun Lee, Suwon-si, KR;

Hojung Lee, Suwon-si, KR;

Saebom Jang, Suwon-si, KR;

Pureum Jung, Suwon-si, KR;

Changho Paeon, Suwon-si, KR;

Assignee:
Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G10L 15/26 (2006.01); G10L 15/16 (2006.01); G10L 15/197 (2013.01);
U.S. Cl.
CPC ...
G10L 15/26 (2013.01); G10L 15/16 (2013.01); G10L 15/197 (2013.01);
Abstract

An electronic apparatus is provided. The electronic apparatus includes a microphone, a memory storing at least one instruction, and a processor connected to the microphone and the memory configured to control the electronic apparatus, and the processor, by executing the at least one instruction, may, based on receiving a user voice signal through the microphone, obtain a text corresponding to the user voice signal, identify a plurality of sentences included in the obtained text, identify a domain corresponding to each of the plurality of sentences among a plurality of domains, based on a similarity of a first sentence and a second sentence, among the plurality of sentences, having a same domain being greater than or equal to a threshold value, obtain a third sentence in which the first sentence and the second sentence are combined by using a first neural network model, and perform natural language understanding for the third sentence.


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