ArticleProceedings of the Conference on Empirical Methods in Natural Language Processing. Conference on Empirical Methods in Natural Language Processing2020
CMU-MOSEAS: A Multimodal Language Dataset for Spanish, Portuguese, German and French.
Article in Proceedings of the Conference on Empirical Methods in Natural Language Processing. Conference on Empirical Methods in Natural Language Processing, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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The trial behind it
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Who cites it
5 citing papers in PubMed.
- Decision level scheme for fusing multiomics and histology slide images using deep neural network for tumor prognosis prediction.Scientific reports · 2025Article
- Developing a Machine Learning-Based Automated Patient Engagement Estimator for Telehealth: Algorithm Development and Validation Study.JMIR formative research · 2025Article
- A dataset for multimodal music information retrieval of Sotho-Tswana musical videos.Data in brief · 2024Article
- Multimodal Sentiment Analysis Representations Learning via Contrastive Learning with Condense Attention Fusion.Sensors (Basel, Switzerland) · 2023Article
- MultiBench: Multiscale Benchmarks for Multimodal Representation Learning.Advances in neural information processing systems · 2021Article
Corrections and comments
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Authors and funding
6 authors.
Funding
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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.