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:
Dec. 26, 2023

Filed:

Apr. 05, 2021
Applicant:

Accenture Global Solutions Limited, Dublin, IE;

Inventors:

Anutosh Maitra, Bangalore, IN;

Shubhashis Sengupta, Bangalore, IN;

Sowmya Rasipuram, Bangalore, IN;

Roshni Ramesh Ramnani, Bangalore, IN;

Junaid Hamid Bhat, Tral, IN;

Sakshi Jain, Bangalore, IN;

Manish Agnihotri, Gwalior, IN;

Dinesh Babu Jayagopi, Bangalore, IN;

Assignee:
Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G10L 15/183 (2013.01); G10L 15/18 (2013.01); G06T 7/70 (2017.01); G10L 25/63 (2013.01); G06F 40/35 (2020.01); G10L 25/57 (2013.01); G10L 15/16 (2006.01); G10L 15/22 (2006.01); G10L 25/90 (2013.01); G06N 3/08 (2023.01); G06N 3/04 (2023.01); A61B 5/16 (2006.01); A61B 5/00 (2006.01); A61B 5/11 (2006.01); G06V 20/40 (2022.01); G06V 40/16 (2022.01); G06N 3/0455 (2023.01);
U.S. Cl.
CPC ...
G10L 15/1815 (2013.01); A61B 5/0077 (2013.01); A61B 5/1107 (2013.01); A61B 5/1114 (2013.01); A61B 5/1128 (2013.01); A61B 5/163 (2017.08); A61B 5/165 (2013.01); A61B 5/4803 (2013.01); A61B 5/7267 (2013.01); G06F 40/35 (2020.01); G06N 3/04 (2013.01); G06N 3/0455 (2023.01); G06N 3/08 (2013.01); G06T 7/70 (2017.01); G06V 20/41 (2022.01); G06V 40/168 (2022.01); G10L 15/16 (2013.01); G10L 15/183 (2013.01); G10L 15/22 (2013.01); G10L 25/57 (2013.01); G10L 25/63 (2013.01); G10L 25/90 (2013.01); G06T 2207/10016 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/30201 (2013.01); G10L 2015/223 (2013.01);
Abstract

A device may receive text data, audio data, and video data associated with a user, and may process the received data, with a first model, to determine a stress level of the user. The device may process the received data, with second models, to determine depression levels of the user, and may combine the depression levels to identify an overall depression level. The device may process the received data, with a third model, to determine a continuous affect prediction, and may process the received data, with a fourth model, to determine an emotion of the user. The device may process the received data, with a fifth model, to determine a response to the user, and may utilize a sixth model to determine a context for the response. The device may utilize seventh models to generate contextual conversation data, and may perform actions based on the contextual conversational data.


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