Automatic Generation of Narrative Content for Digital Games

摘要：

Interactive simulation games used for training usually require a large amount of coherent narrative content. An effective and efficient solution to the narrative content creation problem is to use Natural Language Generation (NLG) systems. The use of NLG systems, however, requires sophisticated linguistic and sometimes programming knowledge. For this reason, NLG systems are typically not accessible to the game designers who write narrative content. We have designed and implemented a visual environment for creating and modifying NLG templates that requires no programming knowledge, and can operate with a minimum of linguistic knowledge. It allows specifying templates with any number of variables and dependencies between them. It automatically generates all the sentences that follow the created template. It uses SimpleNLG to provide the linguistic background knowledge. We tested the performance of our system in the context of an interactive simulation game.

作者: Maria Fernanda CAROPRESO Diana INKPEN Shahzad KHAN Fazel KESHTKAR

作者单位: School of Information Technology and Engineering, University of Ottawa, Ottawa, ON, K1N6N5, Canada DISTIL Interactive, Ottawa, ON, K2H 8R6, Canada

会议类型: 国际会议

会议名称: International Conference on Natural Language Processing and Knowledge Engineering(IEEE自然语言处理与知识工程国际会议 IEEE NLP-KE 2009)

会议地点: 大连

会议语种:英文

页码: 1-8

在线出版日期: 2009-09-24（万方平台首次上网日期，不代表论文的发表时间）