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. 09, 2025

Filed:

Aug. 16, 2023
Applicant:

Capital One Services, Llc, McLean, VA (US);

Inventors:

Joshua Edwards, Philadelphia, PA (US);

Alexander Lin, San Francisco, CA (US);

Mia Rodriguez, Broomfield, CO (US);

Guadalupe Bonilla, Hyattsville, MD (US);

Aysu Ezen Can, Cary, NC (US);

Michael Mossoba, Great Falls, VA (US);

Feng Qiu, West Chester, PA (US);

Tyler Maiman, Melville, NY (US);

Meredith L. Critzer, Midlothian, VA (US);

Assignee:

Capital One Services, LLC, McLean, VA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
H04M 3/00 (2024.01); G10L 15/18 (2013.01); G10L 15/22 (2006.01); H04M 3/51 (2006.01);
U.S. Cl.
CPC ...
H04M 3/5175 (2013.01); G10L 15/1815 (2013.01); G10L 15/22 (2013.01); H04M 2201/39 (2013.01); H04M 2201/40 (2013.01); H04M 2203/403 (2013.01);
Abstract

In some embodiments, the present disclosure provides an exemplary method that may include steps of monitoring, a conversation script between a call center agent and a customer; utilizing, a speech-to-text deep machine learning model to transcribe the audio call to text; utilizing, a natural language processing deep machine learning model to map intent mappings of the audio call; utilizing, a similarity measurement model to determine a semantic similarity between predefined intent mappings and the intent mappings of the call audio text; determining, an error based on the semantic similarity in the intent mapping call audio text; determining a training session based on the error.


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