Multimodal Emotion Recognition

8 repos

Emotion recognition systems that combine multiple data modalities—primarily audio, video/facial expressions, and text—to detect and classify human emotions. This cluster contains Python implementations of multimodal learning architectures, datasets, and models for emotion detection across diverse input sources. Repositories range from foundational multimodal frameworks (MMML, UniMSE) to task-specific systems for audio-visual and compound emotion analysis, reflecting the field's focus on improving emotion classification accuracy by fusing complementary signals.

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