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.
Patent No.:
Date of Patent:
Dec. 05, 2023
Filed:
Mar. 08, 2022
Applicant:
Emerging Automotive, Llc, Los Altos, CA (US);
Inventors:
Angel A. Penilla, Sacramento, CA (US);
Albert S. Penilla, Sunnyvale, CA (US);
Assignee:
Emerging Automotive, LLC, Los Altos, CA (US);
Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G10L 15/22 (2006.01); B60R 16/037 (2006.01); G01C 21/36 (2006.01); G06V 20/59 (2022.01); G06V 40/16 (2022.01); G10L 15/00 (2013.01); G10L 15/06 (2013.01); G10L 15/25 (2013.01); G10L 15/30 (2013.01); G10L 17/04 (2013.01); G10L 25/45 (2013.01); G10L 15/02 (2006.01); G10L 17/06 (2013.01); G10L 21/0208 (2013.01); G10L 25/57 (2013.01); G10L 25/63 (2013.01); G10L 25/84 (2013.01); H04L 67/1097 (2022.01); H04L 67/12 (2022.01); H04L 67/306 (2022.01); G06F 3/01 (2006.01); G10L 25/90 (2013.01); H04L 67/10 (2022.01);
U.S. Cl.
CPC ...
G10L 15/22 (2013.01); B60R 16/0373 (2013.01); G01C 21/3641 (2013.01); G06V 20/597 (2022.01); G06V 40/174 (2022.01); G10L 15/005 (2013.01); G10L 15/02 (2013.01); G10L 15/063 (2013.01); G10L 15/25 (2013.01); G10L 15/30 (2013.01); G10L 17/04 (2013.01); G10L 17/06 (2013.01); G10L 21/0208 (2013.01); G10L 25/45 (2013.01); G10L 25/57 (2013.01); G10L 25/63 (2013.01); G10L 25/84 (2013.01); H04L 67/1097 (2013.01); H04L 67/12 (2013.01); H04L 67/306 (2013.01); G06F 3/013 (2013.01); G06F 3/017 (2013.01); G10L 25/90 (2013.01); G10L 2015/223 (2013.01); G10L 2015/227 (2013.01); G10L 2015/228 (2013.01); H04L 67/10 (2013.01);
Abstract
Methods and systems for determining an emotion of a human driver of a vehicle and using the emotion for generating a vehicle response, is provided. One example method includes processing captured voice data from the human driver over a period of time while the human driver operates the vehicle. The method includes analyzing the voice data to assist in prediction of the emotion of the human driver. The method includes generating the vehicle response. The vehicle response is selected in part based on the emotion that was predicted for the human driver.