Deep learning-based lexical character identification in TV series

IF 0.7 3区 文学 0 HUMANITIES, MULTIDISCIPLINARY Digital Scholarship in the Humanities Pub Date : 2023-10-06 DOI:10.1093/llc/fqad068
Paola Dalla Torre, Paolo Fantozzi, Maurizio Naldi
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Abstract

Abstract Automated character identification in movies and TV series has been typically carried out through face detection in video and the association of faces with characters’ names extracted from dialogues or cast lists. We propose a deep learning architecture to identify characters based on subtitles only, precisely through the lexicon those characters employ. The identification task is formalized as a multi-class classification task. We apply our technique to the complete set of episodes in the Gomorrah TV series and achieve an average identification accuracy beyond 94 per cent on the full set of characters.
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基于深度学习的电视剧词汇特征识别
影视剧中的自动角色识别通常是通过视频中的人脸检测和人脸与从对话或演员名单中提取的角色名字的关联来实现的。我们提出了一种深度学习架构,仅根据字幕识别字符,精确地通过这些字符使用的词汇。识别任务被形式化为一个多类分类任务。我们将我们的技术应用于《蛾摩拉》电视剧的全套剧集,并在全套角色上实现了超过94%的平均识别准确率。
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来源期刊
CiteScore
1.80
自引率
25.00%
发文量
78
期刊介绍: DSH or Digital Scholarship in the Humanities is an international, peer reviewed journal which publishes original contributions on all aspects of digital scholarship in the Humanities including, but not limited to, the field of what is currently called the Digital Humanities. Long and short papers report on theoretical, methodological, experimental, and applied research and include results of research projects, descriptions and evaluations of tools, techniques, and methodologies, and reports on work in progress. DSH also publishes reviews of books and resources. Digital Scholarship in the Humanities was previously known as Literary and Linguistic Computing.
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