Paper Abstract and Keywords |
Presentation |
2021-01-19 10:30
Jerkiness Detection in Spoken Lines of Interactive Characters Using Text-based Speaker Recognition Kota Mori, Komei Arasawa, Shun Hattori (Muroran Inst. of Tech.) IN2020-50 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
In recent years, social-network games have become more and more popular
among young people due to the spread of smartphones. The most attractive features of social-network games are frequent events and story updates.
However, there is a problem that the utterances of characters created in a
short span of time are sometimes inconsistent and uncomfortable. To solve such a problem, this paper proposes a method for identification of
speakers based on their utterances' ending and tone of voice, which are a
part of characters' personality, and evaluates a system for jerkiness
detection based on their utterances' ending and tone of voice using the
method, with respect to several evaluation criteria such as accuracy rate,
and specificity. In addition, this paper aims to develop a system for jerkiness detection based on utterances' ending and tone of voice, by quantitatively evaluating the results of applying jerkiness detection in characters' utterances using the method for identification of speakers based on their utterances' ending and tone of voice to characters' dialogues in derivative works. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
Natural Language Processing / Jerkiness Detection / Feature Extraction / Machine Learning / / / / |
Reference Info. |
IEICE Tech. Rep., vol. 120, no. 311, IN2020-50, pp. 38-42, Jan. 2021. |
Paper # |
IN2020-50 |
Date of Issue |
2021-01-11 (IN) |
ISSN |
Online edition: ISSN 2432-6380 |
Copyright and reproduction |
All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034) |
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IN2020-50 |
Conference Information |
Committee |
IN |
Conference Date |
2021-01-18 - 2021-01-19 |
Place (in Japanese) |
(See Japanese page) |
Place (in English) |
Online |
Topics (in Japanese) |
(See Japanese page) |
Topics (in English) |
Contents Distribution, Social Networking Services, Data Analytics and Processing Platform, Big data, etc. |
Paper Information |
Registration To |
IN |
Conference Code |
2021-01-IN |
Language |
Japanese |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
Jerkiness Detection in Spoken Lines of Interactive Characters Using Text-based Speaker Recognition |
Sub Title (in English) |
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Keyword(1) |
Natural Language Processing |
Keyword(2) |
Jerkiness Detection |
Keyword(3) |
Feature Extraction |
Keyword(4) |
Machine Learning |
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Keyword(6) |
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Keyword(8) |
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1st Author's Name |
Kota Mori |
1st Author's Affiliation |
Muroran Insititute of Technology (Muroran Inst. of Tech.) |
2nd Author's Name |
Komei Arasawa |
2nd Author's Affiliation |
Muroran Insititute of Technology (Muroran Inst. of Tech.) |
3rd Author's Name |
Shun Hattori |
3rd Author's Affiliation |
Muroran Insititute of Technology (Muroran Inst. of Tech.) |
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Speaker |
Author-1 |
Date Time |
2021-01-19 10:30:00 |
Presentation Time |
25 minutes |
Registration for |
IN |
Paper # |
IN2020-50 |
Volume (vol) |
vol.120 |
Number (no) |
no.311 |
Page |
pp.38-42 |
#Pages |
5 |
Date of Issue |
2021-01-11 (IN) |
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