Abstract
This paper presents a task for machine listening comprehension in the argumentation domain and a corresponding dataset in English. We recorded 200 spontaneous speeches arguing for or against 50 controversial topics. For each speech, we formulated a question, aimed at confirming or rejecting the occurrence of potential arguments in the speech. Labels were collected by listening to the speech and marking which arguments were mentioned by the speaker. We applied baseline methods addressing the task, to be used as a benchmark for future work over this dataset. All data used in this work is freely available for research.
Original language | English |
---|---|
Title of host publication | Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, EMNLP 2018 |
Editors | Ellen Riloff, David Chiang, Julia Hockenmaier, Jun'ichi Tsujii |
Publisher | Association for Computational Linguistics |
Pages | 719-724 |
Number of pages | 6 |
ISBN (Electronic) | 9781948087841 |
State | Published - 2018 |
Externally published | Yes |
Event | 2018 Conference on Empirical Methods in Natural Language Processing, EMNLP 2018 - Brussels, Belgium Duration: 31 Oct 2018 → 4 Nov 2018 |
Publication series
Name | Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, EMNLP 2018 |
---|
Conference
Conference | 2018 Conference on Empirical Methods in Natural Language Processing, EMNLP 2018 |
---|---|
Country/Territory | Belgium |
City | Brussels |
Period | 31/10/18 → 4/11/18 |
Bibliographical note
Publisher Copyright:© 2018 Association for Computational Linguistics