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:
Sep. 08, 2026

Filed:

Nov. 15, 2023
Applicant:

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

Inventors:

Hyeontaek Lim, Suwon-si, KR;

Saeyoung Kim, Suwon-si, KR;

Yongkook Kim, Suwon-si, KR;

Boseok Moon, Suwon-si, KR;

Assignee:
Attorney:
Primary Examiner:
Int. Cl.
CPC ...
B25J 9/16 (2006.01); B25J 19/02 (2006.01); G06V 20/50 (2022.01); G06V 40/10 (2022.01); G10L 15/22 (2006.01); H04R 1/02 (2006.01); H04R 1/40 (2006.01); H04R 3/00 (2006.01);
U.S. Cl.
CPC ...
B25J 9/1694 (2013.01); B25J 19/02 (2013.01); B25J 19/026 (2013.01); G06V 20/50 (2022.01); G06V 40/10 (2022.01); G10L 15/22 (2013.01); H04R 1/028 (2013.01); H04R 1/406 (2013.01); H04R 3/005 (2013.01);
Abstract

A robot includes: a light detection and ranging (LiDAR) sensor; a plurality of directional microphones; and at least one processor configured to: identify, based on sensing data obtained through the LiDAR sensor, an object in a vicinity of the robot, identify, based on the type of the object, a weight to apply to an audio signal received through a directional microphone corresponding to a location of the object from among the plurality of directional microphones, obtain context information of the robot based on the sensing data, identify, based on the context information, a pre-processing model corresponding to each directional microphone of the plurality of directional microphones, apply the weight to an audio signal received through the directional microphone corresponding to the location of the object among a plurality of audio signals received through the plurality of directional microphones, obtain a plurality of pre-processed audio signals by inputting the audio signal to which the weight has been applied, and the remaining audio signals into the pre-processing model corresponding to the respective directional microphone, and perform voice recognition based on the plurality of pre-processed audio signals.


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