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Multimodal Sentiment Analysis: Addressing Key Issues and Setting up the Baselines
[article]
2019
arXiv
pre-print
We compile baselines, along with dataset split, for multimodal sentiment analysis. In this paper, we explore three different deep-learning based architectures for multimodal sentiment classification, each improving upon the previous. Further, we evaluate these architectures with multiple datasets with fixed train/test partition. We also discuss some major issues, frequently ignored in multimodal sentiment analysis research, e.g., role of speaker-exclusive models, importance of different
arXiv:1803.07427v2
fatcat:jytchjl3gnbpjkyvp4kb3ih5tu