用户如何编辑计算机生成的视觉故事
On How Users Edit Computer-Generated Visual Stories
摘要：
人工智能（AI）的一个重要研究机构专注于自动生成故事，无论是基于先前的故事情节还是输入图像。然而，文献几乎没有提到用户将如何接收和使用这些故事。考虑到现代人工智能算法生成的故事的质量，用户几乎不可避免地要在真正使用这些故事之前对其进行编辑。在本文中，我们首先分析了人类用户如何编辑机器生成的故事。我们获得了962个由最先进的视觉讲故事模型生成的短篇故事。对于每个故事，我们从Amazon Mechanical Turk招募了五名群众工作者进行编辑。我们对这些编辑的分析表明，平均而言，用户（i）略微缩短了机器生成的故事，（ii）增加了这些故事中的词汇多样性，（iii）经常用代词替换名词及其限定词/冠词。我们的研究更好地了解了用户如何接收和编辑机器生成的故事，为未来的研究人员创建更有用和更有用的故事生成系统提供了信息。
英文摘要：
A significant body of research in Artificial Intelligence (AI) has focused on generating stories automatically, either based on prior story plots or input images. However, literature has little to say about how users would receive and use these stories. Given the quality of stories generated by modern AI algorithms, users will nearly inevitably have to edit these stories before putting them to real use. In this paper, we present the first analysis of how human users edit machine-generated stories. We obtained 962 short stories generated by one of the state-of-the-art visual storytelling models. For each story, we recruited five crowd workers from Amazon Mechanical Turk to edit it. Our analysis of these edits shows that, on average, users (i) slightly shortened machine-generated stories, (ii) increased lexical diversity in these stories, and (iii) often replaced nouns and their determiners/articles with pronouns. Our study provides a better understanding on how users receive and edit machine-generated stories,informing future researchers to create more usable and helpful story generation systems.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
