Papers with CMU Multimodal Opinion Sentiment

2 papers
CMU-MOSEAS: A Multimodal Language Dataset for Spanish, Portuguese, German and French (2020.emnlp-main)

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Challenge: Existing datasets in multimodal language are limited and disproportionately affect native speakers of other languages . authors propose a large-scale dataset for Spanish, Portuguese, German and French .
Approach: They propose a large-scale multimodal language dataset for Spanish, Portuguese, German and French.
Outcome: The proposed dataset 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, emotions, and attributes.
Multimodal Language Analysis in the Wild: CMU-MOSEI Dataset and Interpretable Dynamic Fusion Graph (P18-1)

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Challenge: Analyzing human multimodal language is emerging area of research in NLP.
Approach: They propose a multimodal fusion technique to exploit how modalities interact in multimodal language.
Outcome: The proposed technique exploits how modalities interact with each other in human multimodal language.

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