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:
Dec. 06, 2022

Filed:

Feb. 02, 2018
Applicant:

Nippon Telegraph and Telephone Corporation, Chiyoda-ku, JP;

Inventors:

Atsushi Ando, Yokosuka, JP;

Hosana Kamiyama, Yokosuka, JP;

Satoshi Kobashikawa, Yokosuka, JP;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G10L 25/63 (2013.01); G06N 20/00 (2019.01); G06N 7/00 (2006.01); G06Q 30/00 (2012.01); G10L 15/10 (2006.01); G10L 15/22 (2006.01); G06F 40/20 (2020.01);
U.S. Cl.
CPC ...
G10L 25/63 (2013.01); G06F 40/20 (2020.01); G06N 7/005 (2013.01); G06N 20/00 (2019.01); G06Q 30/016 (2013.01); G10L 15/10 (2013.01); G10L 15/22 (2013.01);
Abstract

State-of-satisfaction change pattern models each including a set of transition weights in state sequences of the states of satisfaction are obtained for predetermined change patterns of the states of satisfaction, and a state-of-satisfaction estimation model for obtaining the posteriori probability of the utterance feature amount given the state of satisfaction of an utterer is obtained by using the utterance-for-learning feature amount and a correct value of the state of satisfaction of an utterer who gave an utterance for learning corresponding to the utterance-for-learning feature amount. By using the input utterance feature amount and the state-of-satisfaction change pattern models and the state-of-satisfaction estimation model, an estimated value of the state of satisfaction of an utterer who gave an utterance corresponding to the input utterance feature amount is obtained.


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