Deep learning-based lexical character identification in TV series.
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...
| Publicado en: | Digital Scholarship in the Humanities Vol. 38; no. 4; pp. 1453 - 1466 |
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| Autores principales: | , , |
| Formato: | Artículo |
| Publicado: |
Oxford University Press / USA
Dec2023
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| Materias: | |
| Acceso en línea: | Ver este registro en EBSCOhost |
| Sumario: | 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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