@inproceedings{mirkin-etal-2018-listening,
title = "Listening Comprehension over Argumentative Content",
author = "Mirkin, Shachar and
Moshkowich, Guy and
Orbach, Matan and
Kotlerman, Lili and
Kantor, Yoav and
Lavee, Tamar and
Jacovi, Michal and
Bilu, Yonatan and
Aharonov, Ranit and
Slonim, Noam",
editor = "Riloff, Ellen and
Chiang, David and
Hockenmaier, Julia and
Tsujii, Jun{'}ichi",
booktitle = "Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing",
month = oct # "-" # nov,
year = "2018",
address = "Brussels, Belgium",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/D18-1078",
doi = "10.18653/v1/D18-1078",
pages = "719--724",
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.",
}
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<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.</abstract>
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%0 Conference Proceedings
%T Listening Comprehension over Argumentative Content
%A Mirkin, Shachar
%A Moshkowich, Guy
%A Orbach, Matan
%A Kotlerman, Lili
%A Kantor, Yoav
%A Lavee, Tamar
%A Jacovi, Michal
%A Bilu, Yonatan
%A Aharonov, Ranit
%A Slonim, Noam
%Y Riloff, Ellen
%Y Chiang, David
%Y Hockenmaier, Julia
%Y Tsujii, Jun’ichi
%S Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing
%D 2018
%8 oct nov
%I Association for Computational Linguistics
%C Brussels, Belgium
%F mirkin-etal-2018-listening
%X 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.
%R 10.18653/v1/D18-1078
%U https://aclanthology.org/D18-1078
%U https://doi.org/10.18653/v1/D18-1078
%P 719-724
Markdown (Informal)
[Listening Comprehension over Argumentative Content](https://aclanthology.org/D18-1078) (Mirkin et al., EMNLP 2018)
ACL
- Shachar Mirkin, Guy Moshkowich, Matan Orbach, Lili Kotlerman, Yoav Kantor, Tamar Lavee, Michal Jacovi, Yonatan Bilu, Ranit Aharonov, and Noam Slonim. 2018. Listening Comprehension over Argumentative Content. In Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, pages 719–724, Brussels, Belgium. Association for Computational Linguistics.