Algorithms for estimation of comic speakers considering reading order of frames and texts

Yuga Omori, Kota Nagamizo, Daisuke Ikeda

研究成果: 書籍/レポート タイプへの寄稿会議への寄与

抄録

Machine learning methods in recent years have focused on multimodal input and cross-modal tasks, and they are used as approaches to problems in various domains. Associating comic texts and characters using these approaches is informative for commercial activities such as speech synthesis and automatic translation of texts. In this study, we address the task of associating a text with a speaker in comics. It is challenging to correspond between them because these are not self-evidently attached, and few studies have attempted. These previous studies have less considered the continuity of comics such as narrative flow or contextual information. We assume that considering the continuity of comics is effective for speaker estimation. This paper proposes algorithms for estimating the reading order of frames or texts, and it also proposes methods for estimating speakers based on these orders. As a result, our proposed method improves accuracy compared to previous methods. Consideration of the frame order is an effective clue to the comic speaker estimation.

本文言語英語
ホスト出版物のタイトルProceedings - 2022 12th International Congress on Advanced Applied Informatics, IIAI-AAI 2022
編集者Tokuro Matsuo, Kunihiko Takamatsu, Yuichi Ono
出版社Institute of Electrical and Electronics Engineers Inc.
ページ367-372
ページ数6
ISBN(電子版)9781665497558
DOI
出版ステータス出版済み - 2022
イベント12th International Congress on Advanced Applied Informatics, IIAI-AAI 2022 - Kanazawa, 日本
継続期間: 7月 2 20227月 7 2022

出版物シリーズ

名前Proceedings - 2022 12th International Congress on Advanced Applied Informatics, IIAI-AAI 2022

会議

会議12th International Congress on Advanced Applied Informatics, IIAI-AAI 2022
国/地域日本
CityKanazawa
Period7/2/227/7/22

!!!All Science Journal Classification (ASJC) codes

  • コンピュータ サイエンスの応用
  • 情報システム
  • 情報システムおよび情報管理
  • 決定科学(その他)

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