A lightweight story-comprehension approach to game dialogue

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“A lightweight story-comprehension approach to game dialogue” by Robert van Leeuwen, Yun-Gyung Cheong, and Mark J. Nelson. In Proceedings of the 1st Workshop on Games and NLP, 2012.

Abstract

In this paper we describe Answery, a rule-based system that allows authors to specify game characters' background stories in natural language. The system parses these background stories, applies transformation rules to turn them into semantic content, and generates dialogue during gameplay by posing it as a question-answering problem. By the means of simple categorization combined with rule inference engine, our system can generate answers efficiently. Our initial pilot study shows that this approach is promising.

BibTeX entry:

@inproceedings{Dialogue:GNLP12,
   author = {Robert van Leeuwen and Yun-Gyung Cheong and Mark J. Nelson},
   title = {A lightweight story-comprehension approach to game dialogue},
   booktitle = {Proceedings of the 1st Workshop on Games and NLP},
   year = {2012}
}

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