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Discourse Annotation of Non-native Spontaneous Spoken Responses Using the Rhetorical Structure Theory Framework

机译:修辞结构理论框架下的非母语自发口语应答的语篇注释

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The availability of the Rhetorical Structure Theory (RST) Discourse Treebank has spurred substantial research into discourse analysis of written texts; however, limited research has been conducted to date on RST annotation and parsing of spoken language, in particular, non-native spontaneous speech. Considering that the measurement of discourse coherence is typically a key metric in human scoring rubrics for assessments of spoken language, we initiated a research effort to obtain RST annotations of a large number of non-native spoken responses from a standardized assessment of academic English proficiency. The resulting inter-annotator k agreements on the three different levels of Span, Nuclear-ity, and Relation are 0.848, 0.766, and 0.653, respectively. Furthermore, a set of features was explored to evaluate the discourse structure of non-native spontaneous speech based on these annotations; the highest performing feature showed a correlation of 0.612 with scores of discourse coherence provided by expert human raters.
机译:修辞结构理论(RST)话语树库的出现刺激了对书面语篇分析的大量研究。但是,到目前为止,关于RST注释和口头语言(特别是非本地自发语音)的解析的研究很少。考虑到语篇连贯性的测量通常是评估语言能力的人类评分标准中的关键指标,因此我们发起了一项研究工作,旨在从学术英语水平的标准化评估中获得大量非母语口语回答的RST注释。由此得出的在“跨度”,“核性”和“关系”三个不同级别上的注释者之间的k协议分别为0.848、0.766和0.653。此外,还基于这些注释探索了一组功能,以评估非母语自发性语音的话语结构。表现最高的功能与专家级评估者提供的话语连贯性得分之间的相关性为0.612。

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