戏剧性对话解缠
Dramatic Conversation Disentanglement
AI总结：
本文构建了基于电影和电视剧的对话解缠数据集，借鉴社会语言学理论定义会话线程并标注了831部电影的万余对话轮次，通过模型对比与大规模应用揭示了戏剧对话中线程长度和性别与话题发起的关系。
摘要：
我们提出了一个新的数据集，用于研究电影和电视剧中的对话解缠。以往的工作主要关注IRC聊天室对话中的对话解缠，而电影和电视剧为研究面对面多方互动中复杂的话语权转换和话题转换语用模式提供了空间。在这项工作中，我们借鉴社会语言学、社会学和电影研究的理论研究，对戏剧文本中的会话线程（包括话语权转换的概念）进行操作化定义，并使用该定义对来自831部电影的10,033个对话轮次（包含2,209个线程）进行标注。我们比较了多个解缠模型在这个戏剧数据集上的表现，并将表现最好的模型应用于808部电影的解缠。我们发现，与预期相反，过去40年中平均线程长度并未显著下降，而由女性演员扮演的角色虽然代表性不足，但相对于其说话时间，她们发起的新会话线程更多。
英文摘要：
We present a new dataset for studying conversation disentanglement in movies and TV series. While previous work has focused on conversation disentanglement in IRC chatroom dialogues, movies and TV shows provide a space for studying complex pragmatic patterns of floor and topic change in face-to-face multi-party interactions. In this work, we draw on theoretical research in sociolinguistics, sociology, and film studies to operationalize a conversational thread (including the notion of a floor change) in dramatic texts, and use that definition to annotate a dataset of 10,033 dialogue turns (comprising 2,209 threads) from 831 movies. We compare the performance of several disentanglement models on this dramatic dataset, and apply the best-performing model to disentangle 808 movies. We see that, contrary to expectation, average thread lengths do not decrease significantly over the past 40 years, and characters portrayed by actors who are women, while underrepresented, initiate more new conversational threads relative to their speaking time.
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。
