Automatic Identification of Character Types from Film Dialogs.

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ID: 60970
2016
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Abstract
We study the detection of character types from fictional dialog texts such as screenplays. As approaches based on the analysis of utterances' linguistic properties are not sufficient to identify all fictional character types, we develop an integrative approach that complements linguistic analysis with interactive and communication characteristics, and show that it can improve the identification performance. The interactive characteristics of fictional characters are captured by the descriptive analysis of semantic graphs weighted by linguistic markers of expressivity and social role. For this approach, we introduce a new data set of action movie character types with their corresponding sequences of dialogs. The evaluation results demonstrate that the integrated approach outperforms baseline approaches on the presented data set. Comparative in-depth analysis of a single screenplay leads on to the discussion of possible limitations of this approach and to directions for future research.
Reference Key
skowron2016automaticapplied Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Skowron, Marcin;Trapp, Martin;Payr, Sabine;Trappl, Robert;
Journal applied artificial intelligence : aai
Year 2016
DOI 10.1080/08839514.2017.1289311
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Keywords
artificial intelligence agents modelling neural networks simulations membrane potential artificial life dependent plasticity neural circuit neuro engineering robots stdp spike timing spiking neurons

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