VivesDebate-Speech: A Corpus of Spoken Argumentation to Leverage Audio Features for Argument Mining

Ramon Ruiz-Dolz, Javier Iranzo-Sánchez


Abstract
In this paper, we describe VivesDebate-Speech, a corpus of spoken argumentation created to leverage audio features for argument mining tasks. The creation of this corpus represents an important contribution to the intersection of speech processing and argument mining communities, and one of the most complete publicly available resources in this topic. Moreover, we have performed a set of first-of-their-kind experiments which show an improvement when integrating audio features into the argument mining pipeline. The provided results can be used as a baseline for future research.
Anthology ID:
2023.emnlp-main.128
Volume:
Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing
Month:
December
Year:
2023
Address:
Singapore
Editors:
Houda Bouamor, Juan Pino, Kalika Bali
Venue:
EMNLP
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
2071–2077
Language:
URL:
https://aclanthology.org/2023.emnlp-main.128
DOI:
10.18653/v1/2023.emnlp-main.128
Bibkey:
Cite (ACL):
Ramon Ruiz-Dolz and Javier Iranzo-Sánchez. 2023. VivesDebate-Speech: A Corpus of Spoken Argumentation to Leverage Audio Features for Argument Mining. In Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, pages 2071–2077, Singapore. Association for Computational Linguistics.
Cite (Informal):
VivesDebate-Speech: A Corpus of Spoken Argumentation to Leverage Audio Features for Argument Mining (Ruiz-Dolz & Iranzo-Sánchez, EMNLP 2023)
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PDF:
https://aclanthology.org/2023.emnlp-main.128.pdf
Video:
 https://aclanthology.org/2023.emnlp-main.128.mp4