从社会情感场景到富有表现力的虚拟叙述者

Roman Miletitch, N. Sabouret, M. Ochs
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引用次数: 3

摘要

讲故事需要将一系列重要事件联系起来,使用陈述来维持紧张感,创造悬念,并为情感发展留出时间。当自动化这个过程时,一个主要的挑战是生成这些填充句,并确保它们与故事充分一致。为此,本文提出了一种局部连贯世界的知识表示模型。我们提出了一种基于概念的本体表示和动态构建概念之间关系的自然语言生成算法的自动讲故事方案。我们的算法扫描场景以构建一个句子骨架,该骨架将使用本体中的伪随机查询进行丰富。这让我们能够在保持故事情节连贯的同时丰富故事内容。最后,我们讨论了我们的评估,并介绍了我们的初步结果。
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From socio-emotional scenarios to expressive virtual narrators
Telling a story requires linking a series of significant events using statements to maintain tension, create suspense and allow time for the development of emotions. When automating this process, one major challenge is the generation of these filling sentences and ensuring that they are sufficiently consistent with the story. To this end we propose in this paper to use a knowledge representation model of a local coherent world. We present a scheme for automatic storytelling based on an ontological representation of concepts and natural language generation algorithms that dynamically build relations between concepts. Our algorithms scan the scenario to build a sentence skeleton that will be enriched using pseudo-random queries in the ontology. This allows us to enrich the story while keeping the storyline coherent. We end by discussing our evaluation and presenting our preliminary results.
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