AI That Understands Feelings Across Text, Voice, and Video
Reading Emotions from Text, Voice, and Video—Together
Meet EGMF, a new AI that reads emotions by combining text, audio, and visuals. Instead of guessing from one signal, it fuses them all and adapts to context—working for both clear-cut emotions (like happy/sad) and nuanced sentiment on a scale.
- Local expert: catches subtle cues—tone shifts, micro-expressions, word choice.
- Correlation expert: links what’s said, how it sounds, and how it looks.
- Global expert: tracks conversation flow and longer-term context.
EGMF plugs into a large language model, so it can explain its judgment in natural language and use the same system for classification or scoring—efficiently fine‑tuned to run on modest hardware.
Tested on English and Chinese benchmarks, it consistently tops prior methods and stays robust across languages, hinting at universal affective patterns. Paper and code: https://arxiv.org/abs/2601.07565v1
Paper: https://arxiv.org/abs/2601.07565v1
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AI EmotionRecognition SentimentAnalysis Multimodal LLM AffectiveComputing NLP Speech Vision CrossLingual Research OpenSource
