论文标题
为情绪吸引讲故事的主角情绪建模
Modeling Protagonist Emotions for Emotion-Aware Storytelling
论文作者
论文摘要
情绪及其演变在创建迷人的故事中起着核心作用。在本文中，我们介绍了关于神经故事讲述中主角的情感轨迹的第一个研究。我们设计的方法会产生遵守故事标题和所需的情感弧线的故事。我们的模型包括情绪监督（EMOSUP）和两个情绪增强（EMORL）模型。 EMORL模型使用特殊的奖励来通过加强学习来定期讲故事过程。我们的自动和手动评估表明，与基线方法相比，这些模型在产生遵循所需情感弧的故事方面要好得多，而不会牺牲故事质量。
Emotions and their evolution play a central role in creating a captivating story. In this paper, we present the first study on modeling the emotional trajectory of the protagonist in neural storytelling. We design methods that generate stories that adhere to given story titles and desired emotion arcs for the protagonist. Our models include Emotion Supervision (EmoSup) and two Emotion-Reinforced (EmoRL) models. The EmoRL models use special rewards designed to regularize the story generation process through reinforcement learning. Our automatic and manual evaluations demonstrate that these models are significantly better at generating stories that follow the desired emotion arcs compared to baseline methods, without sacrificing story quality.
