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:
Apr. 29, 2025

Filed:

Sep. 17, 2021
Applicant:

Optum, Inc., Minnetonka, MN (US);

Inventors:

Vivedha Elango, Chennai, IN;

Soundararajan Dhakshinamoorthy, Chennai, IN;

Srividya Thyagarajan, Chennai, IN;

Ninad D. Sathaye, Bangalore, IN;

Gregory J. Boss, Saginaw, MI (US);

Santhosh Kumar Gopynadhan, Chennai, IN;

Assignee:

Optum, Inc., Minnetonka, MN (US);

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G10L 15/18 (2012.12); G06F 40/279 (2019.12); G06F 40/30 (2019.12); G06N 5/022 (2022.12); G06N 5/04 (2022.12); G06Q 30/016 (2022.12); G10L 15/08 (2005.12); G10L 15/22 (2005.12); G10L 25/63 (2012.12); H04M 3/51 (2005.12);
U.S. Cl.
CPC ...
G10L 15/1815 (2012.12); G06F 40/279 (2019.12); G06F 40/30 (2019.12); G06N 5/022 (2012.12); G06N 5/04 (2012.12); G06Q 30/016 (2012.12); G10L 15/22 (2012.12); G10L 25/63 (2012.12); H04M 3/51 (2012.12); G10L 2015/088 (2012.12);
Abstract

An automated system and corresponding method is configured to predict a call duration of a customer service interaction between a caller and a customer-service agent of a call center, based at least in part on information provided orally by the caller to the automated system. The automated system transcribes the orally provided information, preprocesses the transcribed data, adds feature enrichment data to supplement the transcribed data, and executes a machine-learning model to predict the caller's intent. If the predicted caller's intent does not have an adequate confidence score associated therewith, the system requests additional data from the caller, and supplements the original data with newly provided data, and again determines a predicted call intent. This process may iterate until the confidence score satisfies applicable confidence criteria prior to utilizing two additional machine-learning models to predict a call duration of the interaction between the caller and a customer-service agent.


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