Beyond Acoustic Emotion Recognition: Multimodal Pathos Analysis in Political Speech Using LLM-Based and Acoustic Emotion Models
Researchers have developed a multimodal approach to analyze pathos in political speeches, outperforming traditional acoustic emotion recognition models. The study utilized Gemini 2.5 Flash and an LLM supervisor ensemble, finding Gemini's valence scores strongly correlated with the TRUST-Pathos scores. This LLM-based method proved more effective than acoustic models alone in capturing semantically defined political emotion, though acoustic features still offered insights into arousal levels. AI
IMPACT LLM-based multimodal analysis offers a more nuanced understanding of political speech emotion than acoustic methods alone.