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:
Oct. 29, 2024

Filed:

Dec. 14, 2023
Applicant:

Tethr, Inc., Austin, TX (US);

Inventors:

Thomas Steven Shepherd, Phoneix, AZ (US);

Robert Beasley, Austin, TX (US);

Adam Larsen, Austin, TX (US);

Ross Jones, Frisco, TX (US);

Assignee:

COLLABIP, Inc., Austin, TX (US);

Attorneys:
Primary Examiner:
Int. Cl.
CPC ...
G06Q 10/063 (2023.01); G06F 17/11 (2006.01); G10L 15/18 (2013.01); G10L 15/26 (2006.01); G10L 25/51 (2013.01); H04L 51/02 (2022.01);
U.S. Cl.
CPC ...
G06Q 10/063 (2013.01); G10L 15/1822 (2013.01); G06F 17/11 (2013.01); G10L 15/26 (2013.01); G10L 25/51 (2013.01); H04L 51/02 (2013.01);
Abstract

A conversation control system and associated methods adapt or modify currently active or future conversations and/or interactions based on machine-generated models that continuously evaluate client satisfaction over the entirety of the active conversations and/or interactions. The system receives a conversation with utterances by two or more participants, and generates a vector with features comprised of words, word sequences, and category classifications associated with at least one of the utterances. The system provides the features as inputs to a prediction model that assigns weights to a set of features based on a modeling of different impacts that each feature of the set of features has on one or more aspects of customer satisfaction. The system generates predictions for those aspects of customer satisfaction without input from the participants based on the assigned weights, and performs an automated action based on the one or more predictions.


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