SuperDialseg：用于监督式对话分割的大规模数据集
SuperDialseg: A Large-scale Dataset for Supervised Dialogue Segmentation
AI总结：
本文提出SuperDialseg，一个基于文档对话的大规模监督数据集，含9,478个对话，并提供18个模型的基准，验证了监督学习在对话分割中的有效性及跨域泛化能力。
摘要：
对话分割是对话系统中的一项关键任务，有助于更好地理解对话文本。尽管无监督对话分割方法近期取得了进展，但其性能受到缺乏明确监督训练信号的限制。此外，对话中分割点的精确定义仍是一个具有挑战性的问题，增加了人工标注收集的难度。在本文中，我们借助基于文档的对话（document-grounded dialogues）提供了对话分割点的可行定义，并发布了一个名为SuperDialseg的大规模监督数据集，该数据集基于两个流行的基于文档的对话语料库，包含9,478个对话，并继承了这些语料库中有用的对话相关标注。此外，我们为对话分割任务提供了一个基准，涵盖五个类别的18个模型，并采用了若干合适的评估指标。实证研究表明，监督学习在域内数据集上极为有效，且在SuperDialseg上训练的模型能够在域外数据上展现出良好的泛化能力。此外，我们还在测试集上进行了人工验证，Kappa分数确认了我们自动构建数据集的质量。我们相信，我们的工作是在对话分割领域迈出的重要一步。我们的代码和数据可在以下网址找到：https://github.com/Coldog2333/SuperDialseg。
英文摘要：
Dialogue segmentation is a crucial task for dialogue systems allowing a better understanding of conversational texts. Despite recent progress in unsupervised dialogue segmentation methods, their performances are limited by the lack of explicit supervised signals for training. Furthermore, the precise definition of segmentation points in conversations still remains as a challenging problem, increasing the difficulty of collecting manual annotations. In this paper, we provide a feasible definition of dialogue segmentation points with the help of document-grounded dialogues and release a large-scale supervised dataset called SuperDialseg, containing 9,478 dialogues based on two prevalent document-grounded dialogue corpora, and also inherit their useful dialogue-related annotations. Moreover, we provide a benchmark including 18 models across five categories for the dialogue segmentation task with several proper evaluation metrics. Empirical studies show that supervised learning is extremely effective in in-domain datasets and models trained on SuperDialseg can achieve good generalization ability on out-of-domain data. Additionally, we also conducted human verification on the test set and the Kappa score confirmed the quality of our automatically constructed dataset. We believe our work is an important step forward in the field of dialogue segmentation. Our codes and data can be found from: https://github.com/Coldog2333/SuperDialseg.
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。
