Total for the last 12 months
number of access : ?
number of downloads : ?
ID 116757
Author
Sasayama, Manabu National Institute of Technology, Kagawa College
Keywords
natural language processing
dialogue breakdown
human-computer dialogue system
sentiment analysis
emotion recognition
Content Type
Journal Article
Description
In dialogues between robots or computers and humans, dialogue breakdown analysis is an important tool for achieving better chat dialogues. Conventional dialogue breakdown detection methods focus on semantic variance. Although these methods can detect dialogue breakdowns based on semantic gaps, they cannot always detect emotional breakdowns in dialogues. In chat dialogue systems, emotions are sometimes included in the utterances of the system when responding to the speaker. In this study, we detect emotions from utterances, analyze emotional changes, and use them as the dialogue breakdown feature. The proposed method estimates emotions by utterance unit and generates features by calculating the similarity of the emotions of the utterance and the emotions that have appeared in prior utterances. We employ deep neural networks using sentence distributed representation vectors as the feature. In an evaluation of experimental results, the proposed method achieved a higher dialogue breakdown detection rate when compared to the method using a sentence distributed representation vectors.
Journal Title
Electronics
ISSN
20799292
Publisher
MDPI
Volume
11
Issue
5
Start Page
695
Published Date
2022-02-24
Rights
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
EDB ID
DOI (Published Version)
URL ( Publisher's Version )
FullText File
language
eng
TextVersion
Publisher
departments
Science and Technology