Papers with emotion recognition accuracy
CHEER-Ekman: Fine-grained Embodied Emotion Classification (2025.acl-short)
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| Challenge: | Emotions manifest through physical experiences and bodily reactions, yet identifying such embodied emotions in text remains understudied. |
| Approach: | They propose to extend existing binary embodied emotion dataset with Ekman’s six basic emotion categories. |
| Outcome: | The proposed dataset outperforms existing methods with large language models. |
Beyond Silent Letters: Amplifying LLMs in Emotion Recognition with Vocal Nuances (2025.findings-naacl)
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| Challenge: | Recent studies have demonstrated that Large Language Models possess a form of emotional intelligence, capable of interpreting emotional stimuli in text. |
| Approach: | They propose a method that translates speech characteristics into natural language descriptions and integrates them into LLMs to perform multimodal emotion analysis via text prompts. |
| Outcome: | The proposed method outperforms baseline models that require structural modifications on two datasets showing significant improvements in emotion recognition accuracy. |