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:
Mar. 23, 2021

Filed:

Mar. 05, 2018
Applicant:

Baidu Online Network Technology (Beijing) Co., Ltd., Beijing, CN;

Inventors:

Ying Cao, Beijing, CN;

Xiao Liu, Beijing, CN;

Peng Hu, Beijing, CN;

Jie Zhou, Beijing, CN;

Shilei Wen, Beijing, CN;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G10L 25/30 (2013.01); G10L 15/06 (2013.01); G06N 5/04 (2006.01); G10L 15/02 (2006.01); G06F 16/683 (2019.01); G10L 17/18 (2013.01); G06N 3/04 (2006.01); G06N 3/08 (2006.01); G10L 17/04 (2013.01); G10L 17/02 (2013.01); G06N 7/00 (2006.01);
U.S. Cl.
CPC ...
G10L 25/30 (2013.01); G06F 16/683 (2019.01); G06N 3/0454 (2013.01); G06N 3/08 (2013.01); G06N 5/046 (2013.01); G10L 15/02 (2013.01); G10L 15/063 (2013.01); G10L 17/18 (2013.01); G06N 7/005 (2013.01); G10L 17/02 (2013.01); G10L 17/04 (2013.01);
Abstract

The present disclosure provides a speaker recognition method and apparatus, a computer device and a computer-readable medium. The method comprises: receiving target speech data of a to-be-recognized user in a target group; according to the target speech data, a pre-collected speech database and a pre-trained speaker recognition model, obtaining speech output features corresponding to the target speech data and speech output features corresponding to each of said speech data in the speech database; the speaker recognition model employs a convolution neural network model; recognizing the user corresponding to the target speech data according to the speech output features corresponding to the target speech data and the speech output features corresponding to each of said speech data in the speech database. By employing the speaker recognition model based on the convolution neural network model, the present disclosure can accurately obtain the speech output features of each speech data, thereby more accurately recognizing the user corresponding to the target speech data and thereby substantially improving the efficiency of recognizing speakers.


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