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. 07, 2021

Filed:

Jun. 10, 2020
Applicant:

Invoca, Inc., Santa Barbara, CA (US);

Inventors:

Michael McCourt, Santa Barbara, CA (US);

Sean Storlie, Santa Barbara, CA (US);

Victor Borda, Santa Barbara, CA (US);

Michael Lawrence, Santa Barbara, CA (US);

Anoop Praturu, Santa Barbara, CA (US);

Assignee:

Invoca, Inc., Santa Barbara, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
H04M 3/22 (2006.01); G10L 15/18 (2013.01); G10L 15/197 (2013.01); G06F 16/45 (2019.01); G06N 7/00 (2006.01);
U.S. Cl.
CPC ...
H04M 3/2218 (2013.01); G06F 16/45 (2019.01); G06N 7/005 (2013.01); G10L 15/1815 (2013.01); G10L 15/197 (2013.01);
Abstract

Systems and methods for improving call topic models are described herein. In an embodiment a server computer receives call transcript data comprising an electronic digital representation of a verbal transcription of a call between a first person of a first person type and a second person of a second person type. The server computer splits the call transcript data into first person type data comprising words spoken by the first person in the call and second person type data comprising words spoken by the second person type in the call. The server computer uses a stored topic model to determine a topic of the call, the topic model simultaneously modeling the first person type data as a function of a first probability distribution of words used by the first person type for one or more topics and the second person type data as a function of a second probability distribution of words used by the second person type for the one or more topics, both the first probability distribution of words and the second probability distribution of words being modeled as a function of a third probability distribution of words for the one or more topics. The server computer then stores a data record identifying the topic of the call and/or stores data identifying the topic of the call with the call transcripts.


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