@inproceedings{wang-etal-2019-using,
title = "Using {R}hetorical {S}tructure {T}heory to Assess Discourse Coherence for Non-native Spontaneous Speech",
author = "Wang, Xinhao and
Gyawali, Binod and
Bruno, James V. and
Molloy, Hillary R. and
Evanini, Keelan and
Zechner, Klaus",
editor = "Zeldes, Amir and
Das, Debopam and
Galani, Erick Maziero and
Antonio, Juliano Desiderato and
Iruskieta, Mikel",
booktitle = "Proceedings of the Workshop on Discourse Relation Parsing and Treebanking 2019",
month = jun,
year = "2019",
address = "Minneapolis, MN",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/W19-2719/",
doi = "10.18653/v1/W19-2719",
pages = "153--162",
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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%0 Conference Proceedings
%T Using Rhetorical Structure Theory to Assess Discourse Coherence for Non-native Spontaneous Speech
%A Wang, Xinhao
%A Gyawali, Binod
%A Bruno, James V.
%A Molloy, Hillary R.
%A Evanini, Keelan
%A Zechner, Klaus
%Y Zeldes, Amir
%Y Das, Debopam
%Y Galani, Erick Maziero
%Y Antonio, Juliano Desiderato
%Y Iruskieta, Mikel
%S Proceedings of the Workshop on Discourse Relation Parsing and Treebanking 2019
%D 2019
%8 June
%I Association for Computational Linguistics
%C Minneapolis, MN
%F wang-etal-2019-using
%X 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.
%R 10.18653/v1/W19-2719
%U https://aclanthology.org/W19-2719/
%U https://doi.org/10.18653/v1/W19-2719
%P 153-162
Markdown (Informal)
[Using Rhetorical Structure Theory to Assess Discourse Coherence for Non-native Spontaneous Speech](https://aclanthology.org/W19-2719/) (Wang et al., NAACL 2019)
ACL