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, Klaus Zechner

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.
Anthology ID:
W19-2719
Volume:
Proceedings of the Workshop on Discourse Relation Parsing and Treebanking 2019
Month:
June
Year:
2019
Address:
Minneapolis, MN
Venue:
NAACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
153–162
Language:
URL:
https://aclanthology.org/W19-2719
DOI:
10.18653/v1/W19-2719
Bibkey:
Cite (ACL):
Xinhao Wang, Binod Gyawali, James V. Bruno, Hillary R. Molloy, Keelan Evanini, and Klaus Zechner. 2019. Using Rhetorical Structure Theory to Assess Discourse Coherence for Non-native Spontaneous Speech. In Proceedings of the Workshop on Discourse Relation Parsing and Treebanking 2019, pages 153–162, Minneapolis, MN. Association for Computational Linguistics.
Cite (Informal):
Using Rhetorical Structure Theory to Assess Discourse Coherence for Non-native Spontaneous Speech (Wang et al., NAACL 2019)
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