Using Rhetorical Structure Theory to Assess Discourse Coherence for Non-native Spontaneous Speech

Xinhao Wang, Binod Gyawali, James V. Bruno, Hillary R. Molloy, Keelan Evanini, K. Zechner
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引用次数: 9

Abstract

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 conducted research to obtain RST annotations on non-native spoken responses from a standardized assessment of academic English proficiency. Subsequently, automatic parsers were trained on these annotations to process non-native spontaneous speech. Finally, a set of features were extracted from automatically generated RST trees to evaluate the discourse structure of non-native spontaneous speech, which were then employed to further improve the validity of an automated speech scoring system.
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运用修辞结构理论评价非母语自发语篇连贯
本研究的目的是在非英语母语者英语口语水平评估的背景下,建立自发口语反应的话语结构模型。修辞结构理论(RST)是分析书面语篇组织的常用理论。然而,到目前为止,对口语,特别是非母语自发语音的RST注释和解析的研究还很有限。由于语篇连贯的测量通常是口语评估的人类评分标准中的一个关键指标,我们进行了一项研究,从学术英语水平的标准化评估中获得非母语口语反应的RST注释。随后,在这些注释上训练自动解析器来处理非母语自发语音。最后,从自动生成的RST树中提取一组特征来评价非母语自发语音的语篇结构,进一步提高自动语音评分系统的有效性。
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