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Discourse Modeling of Non-Native Spontaneous Speech Using the Rhetorical Structure Theory Framework

机译:修辞结构理论框架下的非母语自发性言语建模

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摘要

This study aims to model the discourse structure of spontaneous spoken responses within the context of an assessment of English speaking proficiency for non-native speakers. Rhetorical Structure Theory (RST) has been commonly used in the analysis of discourse organization 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. Due to the fact that the measurement of discourse coherence is typically a key metric in human scoring rubrics for assessments of spoken language, we initiated a research to first obtain RST annotations on non-native spoken responses from a standardized assessment of academic English proficiency. Afterwards, based on the annotations obtained, automatic parsers were built to process non-native spontaneous speech. Finally, a set of effective features were extracted from both manually annotated and automatically generated RST trees to evaluate the discourse structure of non-native spontaneous speech, and then employed to further improve the validity of an automated speech scoring system.
机译:本研究旨在在评估非母语人士英语熟练程度的背景下,对自发性口语回应的话语结构进行建模。修辞结构理论(RST)通常用于分析书面语篇的组织结构。但是,迄今为止,关于RST语言的注释和解析(特别是非母语自发性语音)的研究很少。由于话语连贯性的度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,首先从学术英语水平的标准化评估中获得关于非母语言语反应的RST注释。然后,基于获得的注释,构建自动解析器以处理非本地自发语音。最后,从人工注释和自动生成的RST树中提取了一组有效特征,以评估非本地自发语音的话语结构,然后用于进一步提高自动语音评分系统的有效性。

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