论文标题
通过因果，常识地订购自动讲故事
Automated Storytelling via Causal, Commonsense Plot Ordering
论文作者
论文摘要
自动故事情节生成是生成一致的情节事件序列的任务。据信，情节事件之间的因果关系会增加故事和情节连贯性的看法。在这项工作中，我们将软性因果关系的概念介绍为从常识性推理推断出的因果关系。我们演示了C2PO，这是一种叙事生成的方法，该方法通过因果，常识情节排序来实现这一概念。使用人参与方案，我们针对具有不同常识性推理和归纳偏见的基线系统评估系统，以确定软性因果关系在感知的故事质量中的作用。通过这些研究，我们还探讨了讲故事类型的常识性规范如何影响故事质量的看法的相互作用。
Automated story plot generation is the task of generating a coherent sequence of plot events. Causal relations between plot events are believed to increase the perception of story and plot coherence. In this work, we introduce the concept of soft causal relations as causal relations inferred from commonsense reasoning. We demonstrate C2PO, an approach to narrative generation that operationalizes this concept through Causal, Commonsense Plot Ordering. Using human-participant protocols, we evaluate our system against baseline systems with different commonsense reasoning reasoning and inductive biases to determine the role of soft causal relations in perceived story quality. Through these studies we also probe the interplay of how changes in commonsense norms across storytelling genres affect perceptions of story quality.
