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:
Nov. 10, 2020

Filed:

Mar. 08, 2018
Applicant:

International Business Machines Corporation, Armonk, NY (US);

Inventors:

Chulaka Gunasekara, Yorktown Heights, NY (US);

David Nahamoo, Great Neck, NY (US);

Lazaros Polymenakos, West Harrison, NY (US);

Kshitij Fadnis, White Plains, NY (US);

David Echeverria Ciaurri, New York, NY (US);

Jatin Ganhotra, White Plains, NY (US);

Attorneys:
Primary Examiner:
Int. Cl.
CPC ...
G10L 15/06 (2013.01); G06N 3/08 (2006.01); G06N 3/04 (2006.01); G10L 15/14 (2006.01); G10L 15/183 (2013.01); G10L 15/16 (2006.01); G06F 16/9032 (2019.01); G06F 40/35 (2020.01); G06F 40/216 (2020.01); G06F 40/284 (2020.01); H04L 12/58 (2006.01);
U.S. Cl.
CPC ...
G10L 15/063 (2013.01); G06F 16/90332 (2019.01); G06F 40/216 (2020.01); G06F 40/284 (2020.01); G06F 40/35 (2020.01); G06N 3/0445 (2013.01); G06N 3/0472 (2013.01); G06N 3/08 (2013.01); G10L 15/14 (2013.01); G10L 15/16 (2013.01); G10L 15/183 (2013.01); H04L 51/02 (2013.01);
Abstract

A method, program product and computer system to predict utterances in a dialog system includes receiving a set of utterances associated with a dialog between a client device and a dialog system, mapping the utterances to vector representations of the utterances, and identifying at least one cluster to which the utterances belong from among a plurality of possible clusters. A next cluster is predicted based upon a conditional probability of the next cluster following a set of a predetermined number of previous clusters using a language model. A next utterance is predicted from among a plurality of possible utterances within the predicted next cluster.


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