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  1. 論文誌(ジャーナル)
  2. Vol.62
  3. No.1

Methods for Efficiently Constructing Text-dialogue-agent System using Existing Anime Characters

https://ipsj.ixsq.nii.ac.jp/records/208969
https://ipsj.ixsq.nii.ac.jp/records/208969
d06da329-e1dc-4579-b365-4f53d9d5c145
名前 / ファイル ライセンス アクション
IPSJ-JNL6201006.pdf IPSJ-JNL6201006.pdf (5.5 MB)
Copyright (c) 2021 by the Information Processing Society of Japan
オープンアクセス
Item type Journal(1)
公開日 2021-01-15
タイトル
タイトル Methods for Efficiently Constructing Text-dialogue-agent System using Existing Anime Characters
タイトル
言語 en
タイトル Methods for Efficiently Constructing Text-dialogue-agent System using Existing Anime Characters
言語
言語 eng
キーワード
主題Scheme Other
主題 [特集:持続可能な社会を実現するコラボレーション技術とネットワークサービス] text-dialogue-agent system, existing anime character, efficient construction method, utterance generation, motion generation
資源タイプ
資源タイプ識別子 http://purl.org/coar/resource_type/c_6501
資源タイプ journal article
著者所属
NTT Media Intelligence Laboratories, NTT Corporation
著者所属
NTT Media Intelligence Laboratories, NTT Corporation
著者所属
NTT Media Intelligence Laboratories, NTT Corporation
著者所属
NTT Media Intelligence Laboratories, NTT Corporation
著者所属
NTT Communication Science Laboratories, NTT Corporation
著者所属
NTT Media Intelligence Laboratories, NTT Corporation
著者所属
DWANGO Co., Ltd.
著者所属
DWANGO Co., Ltd.
著者所属
DWANGO Co., Ltd.
著者所属
NTT Media Intelligence Laboratories, NTT Corporation
著者所属(英)
en
NTT Media Intelligence Laboratories, NTT Corporation
著者所属(英)
en
NTT Media Intelligence Laboratories, NTT Corporation
著者所属(英)
en
NTT Media Intelligence Laboratories, NTT Corporation
著者所属(英)
en
NTT Media Intelligence Laboratories, NTT Corporation
著者所属(英)
en
NTT Communication Science Laboratories, NTT Corporation
著者所属(英)
en
NTT Media Intelligence Laboratories, NTT Corporation
著者所属(英)
en
DWANGO Co., Ltd.
著者所属(英)
en
DWANGO Co., Ltd.
著者所属(英)
en
DWANGO Co., Ltd.
著者所属(英)
en
NTT Media Intelligence Laboratories, NTT Corporation
著者名 Ryo, Ishii

× Ryo, Ishii

Ryo, Ishii

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Ryuichiro, Higashinaka

× Ryuichiro, Higashinaka

Ryuichiro, Higashinaka

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Koh, Mitsuda

× Koh, Mitsuda

Koh, Mitsuda

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Taichi, Katayama

× Taichi, Katayama

Taichi, Katayama

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Masahiro, Mizukami

× Masahiro, Mizukami

Masahiro, Mizukami

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Junji, Tomita

× Junji, Tomita

Junji, Tomita

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Hidetoshi, Kawabata

× Hidetoshi, Kawabata

Hidetoshi, Kawabata

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Emi, Yamaguchi

× Emi, Yamaguchi

Emi, Yamaguchi

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Noritake, Adachi

× Noritake, Adachi

Noritake, Adachi

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Yushi, Aono

× Yushi, Aono

Yushi, Aono

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著者名(英) Ryo, Ishii

× Ryo, Ishii

en Ryo, Ishii

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Ryuichiro, Higashinaka

× Ryuichiro, Higashinaka

en Ryuichiro, Higashinaka

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Koh, Mitsuda

× Koh, Mitsuda

en Koh, Mitsuda

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Taichi, Katayama

× Taichi, Katayama

en Taichi, Katayama

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Masahiro, Mizukami

× Masahiro, Mizukami

en Masahiro, Mizukami

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Junji, Tomita

× Junji, Tomita

en Junji, Tomita

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Hidetoshi, Kawabata

× Hidetoshi, Kawabata

en Hidetoshi, Kawabata

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Emi, Yamaguchi

× Emi, Yamaguchi

en Emi, Yamaguchi

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Noritake, Adachi

× Noritake, Adachi

en Noritake, Adachi

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Yushi, Aono

× Yushi, Aono

en Yushi, Aono

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論文抄録
内容記述タイプ Other
内容記述 Starting from their early years, many persons dream of being able to chat with their favorite anime characters. To make such a dream possible, we propose an efficient method for constructing a system that enables users to text chat with existing anime characters. We tackled two research problems to generate verbal and nonverbal behaviors for a text-chat agent system utilizing an existing character. A major issue in creating verbal behavior is generating utterance text that reflects the personality of existing characters in response to any user questions. To cope with this problem we propose use of role play-based question-answering to efficiently collect high-quality paired data of user questions and system answers reflecting the personality of an anime character. We also propose a new utterance generation method that uses a neural translation model with the collected data. Rich and natural expressions of nonverbal behavior greatly enhance the appeal of agent systems. However, not all existing anime characters move as naturally and as diversely as humans. Therefore, we propose a method that can automatically generate whole-body motion from spoken text in order to give the anime characters natural, human-like movements. In addition to these movements, we try to add a small amount of characteristic movement on a rule basis to reflect personality. We created a text-dialogue agent system of a popular existing anime character using our proposed generation methods. As a result of a subjective evaluation of the implemented system, our methods for generating verbal and nonverbal behavior improved the impression of the agent's responsiveness and reflected the personality of the character. Since generating characteristic motions with a small amount of characteristic movement on the basis of heuristic rules was not effective, our proposed motion generation method which can generate the average motion of many people, is useful for generating motion for existing anime characters. Therefore, our proposed methods for generating verbal and nonverbal behaviors and the system-construction method are likely to prove a powerful tool for achieving text-dialogue agent systems for existing characters.
------------------------------
This is a preprint of an article intended for publication Journal of
Information Processing(JIP). This preprint should not be cited. This
article should be cited as: Journal of Information Processing Vol.29(2021) (online)
DOI http://dx.doi.org/10.2197/ipsjjip.29.30
------------------------------
論文抄録(英)
内容記述タイプ Other
内容記述 Starting from their early years, many persons dream of being able to chat with their favorite anime characters. To make such a dream possible, we propose an efficient method for constructing a system that enables users to text chat with existing anime characters. We tackled two research problems to generate verbal and nonverbal behaviors for a text-chat agent system utilizing an existing character. A major issue in creating verbal behavior is generating utterance text that reflects the personality of existing characters in response to any user questions. To cope with this problem we propose use of role play-based question-answering to efficiently collect high-quality paired data of user questions and system answers reflecting the personality of an anime character. We also propose a new utterance generation method that uses a neural translation model with the collected data. Rich and natural expressions of nonverbal behavior greatly enhance the appeal of agent systems. However, not all existing anime characters move as naturally and as diversely as humans. Therefore, we propose a method that can automatically generate whole-body motion from spoken text in order to give the anime characters natural, human-like movements. In addition to these movements, we try to add a small amount of characteristic movement on a rule basis to reflect personality. We created a text-dialogue agent system of a popular existing anime character using our proposed generation methods. As a result of a subjective evaluation of the implemented system, our methods for generating verbal and nonverbal behavior improved the impression of the agent's responsiveness and reflected the personality of the character. Since generating characteristic motions with a small amount of characteristic movement on the basis of heuristic rules was not effective, our proposed motion generation method which can generate the average motion of many people, is useful for generating motion for existing anime characters. Therefore, our proposed methods for generating verbal and nonverbal behaviors and the system-construction method are likely to prove a powerful tool for achieving text-dialogue agent systems for existing characters.
------------------------------
This is a preprint of an article intended for publication Journal of
Information Processing(JIP). This preprint should not be cited. This
article should be cited as: Journal of Information Processing Vol.29(2021) (online)
DOI http://dx.doi.org/10.2197/ipsjjip.29.30
------------------------------
書誌レコードID
収録物識別子タイプ NCID
収録物識別子 AN00116647
書誌情報 情報処理学会論文誌

巻 62, 号 1, 発行日 2021-01-15
ISSN
収録物識別子タイプ ISSN
収録物識別子 1882-7764
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