CMU-MOSEAS: A Multimodal Language Dataset for Spanish, Portuguese, German and French

AmirAli Bagher Zadeh, Yansheng Cao, Simon Hessner, Paul Pu Liang, Soujanya Poria, Louis-Philippe Morency


Abstract
Modeling multimodal language is a core research area in natural language processing. While languages such as English have relatively large multimodal language resources, other widely spoken languages across the globe have few or no large-scale datasets in this area. This disproportionately affects native speakers of languages other than English. As a step towards building more equitable and inclusive multimodal systems, we introduce the first large-scale multimodal language dataset for Spanish, Portuguese, German and French. The proposed dataset, called CMU-MOSEAS (CMU Multimodal Opinion Sentiment, Emotions and Attributes), is the largest of its kind with 40,000 total labelled sentences. It covers a diverse set topics and speakers, and carries supervision of 20 labels including sentiment (and subjectivity), emotions, and attributes. Our evaluations on a state-of-the-art multimodal model demonstrates that CMU-MOSEAS enables further research for multilingual studies in multimodal language.
Anthology ID:
2020.emnlp-main.141
Volume:
Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)
Month:
November
Year:
2020
Address:
Online
Editors:
Bonnie Webber, Trevor Cohn, Yulan He, Yang Liu
Venue:
EMNLP
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
1801–1812
Language:
URL:
https://aclanthology.org/2020.emnlp-main.141
DOI:
10.18653/v1/2020.emnlp-main.141
Bibkey:
Cite (ACL):
AmirAli Bagher Zadeh, Yansheng Cao, Simon Hessner, Paul Pu Liang, Soujanya Poria, and Louis-Philippe Morency. 2020. CMU-MOSEAS: A Multimodal Language Dataset for Spanish, Portuguese, German and French. In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), pages 1801–1812, Online. Association for Computational Linguistics.
Cite (Informal):
CMU-MOSEAS: A Multimodal Language Dataset for Spanish, Portuguese, German and French (Bagher Zadeh et al., EMNLP 2020)
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https://preview.aclanthology.org/landing_page/2020.emnlp-main.141.pdf
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