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M-Arg: MultiModal Argument Mining Dataset for Political Debates with Audio and Transcripts

M-Arg: MultiModal Argument Mining Dataset for Political Debates with Audio and Transcripts
M-Arg: MultiModal Argument Mining Dataset for Political Debates with Audio and Transcripts
This dataset contains audio/transcripts from 5 US 2020 presidential debates annotated for argumentation mining tasks, in particular for support and attack relations. The data is presented as audio + aligned transcripts to be used in multimodal applications. The annotations were done with crowdsourcing techniques.
University of Southampton
Mestre, Rafael
33721a01-ab1a-4f71-8b0e-abef8afc92f3
Milicin, Razvan
bcc0599d-114a-4cd0-8fc9-202421b69caa
Middleton, Stuart
404b62ba-d77e-476b-9775-32645b04473f
Ryan, Matthew
f07cd3e8-f3d9-4681-9091-84c2df07cd54
Zhu, Jiatong
52569115-5d72-4fc0-8876-a66b991ed209
Norman, Timothy
663e522f-807c-4569-9201-dc141c8eb50d
Mestre, Rafael
33721a01-ab1a-4f71-8b0e-abef8afc92f3
Milicin, Razvan
bcc0599d-114a-4cd0-8fc9-202421b69caa
Middleton, Stuart
404b62ba-d77e-476b-9775-32645b04473f
Ryan, Matthew
f07cd3e8-f3d9-4681-9091-84c2df07cd54
Zhu, Jiatong
52569115-5d72-4fc0-8876-a66b991ed209
Norman, Timothy
663e522f-807c-4569-9201-dc141c8eb50d

Mestre, Rafael, Milicin, Razvan, Middleton, Stuart, Ryan, Matthew, Zhu, Jiatong and Norman, Timothy (2021) M-Arg: MultiModal Argument Mining Dataset for Political Debates with Audio and Transcripts. University of Southampton doi:10.5281/zenodo.5653503 [Dataset]

Record type: Dataset

Abstract

This dataset contains audio/transcripts from 5 US 2020 presidential debates annotated for argumentation mining tasks, in particular for support and attack relations. The data is presented as audio + aligned transcripts to be used in multimodal applications. The annotations were done with crowdsourcing techniques.

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m_arg_multimodal_argumentation_dataset_v1.0.0.zip - Dataset
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More information

Published date: 10 November 2021
Related URLs:
Learn more about Agents, Interactions and Complexity research Learn more about School of Electronics and Computer Science research

Identifiers

Local EPrints ID: 452068
URI: http://eprints.soton.ac.uk/id/eprint/452068
DOI: doi:10.5281/zenodo.5653503
PURE UUID: 598fde6f-f0d8-4148-939c-41e273508977
ORCID for Rafael Mestre: ORCID iD orcid.org/0000-0002-2460-4234
ORCID for Stuart Middleton: ORCID iD orcid.org/0000-0001-8305-8176
ORCID for Matthew Ryan: ORCID iD orcid.org/0000-0002-8693-5063
ORCID for Timothy Norman: ORCID iD orcid.org/0000-0002-6387-4034

Catalogue record

Date deposited: 10 Nov 2021 17:35
Last modified: 14 Sep 2023 01:58

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Contributors

Creator: Rafael Mestre ORCID iD
Creator: Razvan Milicin
Creator: Stuart Middleton ORCID iD
Creator: Matthew Ryan ORCID iD
Creator: Jiatong Zhu
Creator: Timothy Norman ORCID iD

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