wenliangdai/Modality-Transferable-MER
Modality-Transferable-MER, multimodal emotion recognition model with zero-shot and few-shot abilities.
This project helps researchers and developers understand emotions from various sources like spoken language, facial expressions, and text. It takes audio, visual, and textual data as input and determines the emotional content, even for emotions it hasn't seen much of before. Social science researchers, human-computer interaction designers, and AI developers working on emotion-aware systems would find this useful.
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Use this if you need to analyze emotions across different data types (like voice, video, and text) and are dealing with limited examples for certain emotions or entirely new emotion categories.
Not ideal if you only work with a single data type, have abundant labeled data for all emotion categories, or require real-time, low-latency emotion detection in a production environment without further optimization.
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Language
Python
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CC-BY-4.0
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Last pushed
Apr 23, 2021
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