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    <abstract>Interactive story systems often involve dialogue with virtual dramatic characters. However, to date most character dialogue is written by hand. One way to ease the authoring process is to (semi-)automatically generate dialogue based on film characters. We extract features from dialogue of film characters in leading roles. Then we use these character-based features to drive our language generator to produce interesting utterances. This paper describes a corpus of film dialogue that we have collected from the IMSDb archive and annotated for linguistic structures and character archetypes. We extract different sets of features using external sources such as LIWC and SentiWordNet as well as using our own written scripts. The automation of feature extraction also eases the process of acquiring additional film scripts. We briefly show how film characters can be represented by models learned from the corpus, how the models can be distinguished based on different categories such as gender and film genre, and how they can be applied to a language generator to generate utterances that can be perceived as being similar to the intended character model.</abstract>
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%0 Conference Proceedings
%T An Annotated Corpus of Film Dialogue for Learning and Characterizing Character Style
%A Walker, Marilyn
%A Lin, Grace
%A Sawyer, Jennifer
%Y Calzolari, Nicoletta
%Y Choukri, Khalid
%Y Declerck, Thierry
%Y Doğan, Mehmet Uğur
%Y Maegaard, Bente
%Y Mariani, Joseph
%Y Moreno, Asuncion
%Y Odijk, Jan
%Y Piperidis, Stelios
%S Proceedings of the Eighth International Conference on Language Resources and Evaluation (LREC‘12)
%D 2012
%8 May
%I European Language Resources Association (ELRA)
%C Istanbul, Turkey
%F walker-etal-2012-annotated
%X Interactive story systems often involve dialogue with virtual dramatic characters. However, to date most character dialogue is written by hand. One way to ease the authoring process is to (semi-)automatically generate dialogue based on film characters. We extract features from dialogue of film characters in leading roles. Then we use these character-based features to drive our language generator to produce interesting utterances. This paper describes a corpus of film dialogue that we have collected from the IMSDb archive and annotated for linguistic structures and character archetypes. We extract different sets of features using external sources such as LIWC and SentiWordNet as well as using our own written scripts. The automation of feature extraction also eases the process of acquiring additional film scripts. We briefly show how film characters can be represented by models learned from the corpus, how the models can be distinguished based on different categories such as gender and film genre, and how they can be applied to a language generator to generate utterances that can be perceived as being similar to the intended character model.
%U https://aclanthology.org/L12-1657/
%P 1373-1378

Markdown (Informal)

[An Annotated Corpus of Film Dialogue for Learning and Characterizing Character Style](https://aclanthology.org/L12-1657/) (Walker et al., LREC 2012)

• An Annotated Corpus of Film Dialogue for Learning and Characterizing Character Style (Walker et al., LREC 2012)

ACL

• Marilyn Walker, Grace Lin, and Jennifer Sawyer. 2012. An Annotated Corpus of Film Dialogue for Learning and Characterizing Character Style. In Proceedings of the Eighth International Conference on Language Resources and Evaluation (LREC'12), pages 1373–1378, Istanbul, Turkey. European Language Resources Association (ELRA).