TMFN: a text-based multimodal fusion network with multi-scale feature extraction and unsupervised contrastive learning for multimodal sentiment analysis
Abstract Multimodal sentiment analysis (MSA) is crucial in human-computer interaction. Current methods use simple sub-models for feature extraction, neglecting multi-scale features and the complexity of emotions. Text, visual, and audio each have unique characteristics in MSA, with text often provid...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Springer
2025-01-01
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| Series: | Complex & Intelligent Systems |
| Subjects: | |
| Online Access: | https://doi.org/10.1007/s40747-024-01724-5 |
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