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:
Nov. 16, 2021

Filed:

Jan. 10, 2020
Applicant:

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

Inventors:

Chengjun Wang, Nanjing, CN;

Xin Liu, Nanjing, CN;

Feng Tang, Nanjing, CN;

Suxia Li, Nanjing, CN;

Bo Peng, Nanjing, CN;

Lei Wan, Nanjing, CN;

Assignee:
Attorney:
Primary Examiner:
Int. Cl.
CPC ...
H04M 3/22 (2006.01); H04M 3/42 (2006.01); G06N 3/08 (2006.01);
U.S. Cl.
CPC ...
H04M 3/2281 (2013.01); G06N 3/08 (2013.01); H04M 3/42059 (2013.01); H04M 2203/6027 (2013.01); H04M 2203/6045 (2013.01); H04M 2203/6054 (2013.01);
Abstract

A method and an apparatus for detecting an abnormality of a caller are provided. The method includes at the beginning of a call, acquiring, by a terminal device, real voice/video data of a call object who needs abnormality detection and a corresponding pre-trained multi-stage neural network detection model, during the call, collecting, by the terminal device, call data according to a preset data collection policy, for each call object, inputting the currently collected call data and the real voice/video data of the call object into the model of the call object, and determining whether the call object is abnormal according to a detection result output by the model, in which the call data includes image data and/or voice data, and an identification manner adopted by the model includes face identification, voiceprint identification, limb movement identification, and/or lip language identification. By adopting the disclosure, the abnormality of the caller may be accurately detected, and the voice forgery and the video forgery mimicked by AI during a call may be accurately identified.


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