CMU-MOSEAS: A Multimodal Language Dataset for Spanish, Portuguese, German and French.
CMU-MOSEAS: A Multimodal Language Dataset for Spanish, Portuguese, German and French.
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DOI：
10.18653/v1/2020.emnlp-main.141
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发表时间：
2020-11
期刊：
影响因子：
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通讯作者：
Morency LP
中科院分区：
文献类型：
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作者：
Zadeh A;Cao YS;Hessner S;Liang PP;Poria S;Morency LP
多模态语言建模是自然语言处理的核心研究领域。虽然英语等语言具有相对较大的多模态语言资源，但地球仪上其他广泛使用的语言在这一领域几乎没有或没有大规模的数据集。这不成比例地影响到英语以外的其他语言的母语者。作为建立更加公平和包容的多模式系统的一步，我们介绍了西班牙语，葡萄牙语，德语和法语的第一个大规模多模式语言数据集。该数据集名为CMU-MOSEAS（CMU Multimodal Opinion Sentiment，Emotions and Attributes），是同类数据集中最大的，共有40，000个标记句子。它涵盖了不同的主题和演讲者，并对20个标签进行了监督，包括情感（和主观性），情感和属性。我们对最先进的多模态模型的评估表明，CMU-MOSEAS可以进一步研究多模态语言的多语种研究。
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.