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The Discussion Corpus toward Argumentation Quality Assessment in Multi-Party Conversation

机译:多党对话中的论证质量评估讨论语料库

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Recently, many studies in NLP, especially argument mining, have focused on revealing what a good argument is with written texts. However, there are a few studies to challenge argumentation quality assessment in face-to-face conversations due to a lack of corpora, as compared with written texts. Therefore, we construct a multimodal multi-party discussion corpus toward argumentation quality assessment in multi-party conversation. The corpus consists of 10 multi-party discussions (200 minutes) in total. Each participant is annotated for 6 scores about rhetoric, which is one of the classes of argumentation quality. In this paper, we explain the procedure of our corpus construction and report the results of the annotation.
机译:最近,在NLP中的许多研究,特别是争论挖掘,都集中在揭示了良好的论据与书面文本有什么关系。 然而,与书面文本相比,有一些研究可以在面对面对话中挑战面对面对话中的争议质量评估。 因此,我们构建了多级多方讨论语料库,朝着多方对话中的论证质量评估。 语料库总共包括10个多方讨论(200分钟)。 每个参与者都有6个关于言论的6分,这是争论质量的阶级之一。 在本文中,我们解释了我们的语料库建设的程序,并报告了注释结果。

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