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. 28, 2021

Filed:

Dec. 28, 2020
Applicant:

Cresta Intelligence Inc., San Francisco, CA (US);

Inventors:

Tianlin Shi, Menlo Park, CA (US);

Peter Elliot Schmidt-Nielsen, Menlo Park, CA (US);

Navjot Matharu, San Francisco, CA (US);

Alexander Donald Roe, San Francisco, CA (US);

JungHa Lee, Sunnyvale, CA (US);

Syed Zayd Enam, San Francisco, CA (US);

Assignee:

CRESTA INTELLIGENCE INC., San Francisco, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
H04M 3/51 (2006.01); G06N 3/08 (2006.01); G06Q 10/06 (2012.01); G06N 20/00 (2019.01); H04M 3/523 (2006.01);
U.S. Cl.
CPC ...
H04M 3/5175 (2013.01); G06N 3/08 (2013.01); G06N 20/00 (2019.01); G06Q 10/06393 (2013.01); G06Q 10/06395 (2013.01); G06Q 10/06398 (2013.01); H04M 3/5232 (2013.01); H04M 2203/402 (2013.01);
Abstract

A conversation may be monitored in real time using a trained machine learning model. This real-time monitoring may detect attributes of a conversation, such as a conversation type, a state of a conversation, as well as other attributes that help specify a context of a conversation. Contextually appropriate behavioral targets may be provided by machine learning model to an agent participating in a conversation. In some embodiments, these 'behavioral targets' are identified by applying a set of rules to the contemporaneously identified conversation attributes. The behavioral targets may be defined in advance prior to the start of a conversation. In this way, the machine learning model may be trained to associate particular behavioral target(s) with one or more conversation attributes (or collections of attributes). This facilitates the real-time monitoring of a conversation and contemporaneous guidance of an agent with machine-identified behavioral targets.


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