EmotionAI: A Privacy-Preserving Computational Intelligence Pipeline for Speech-Emotion-Grounded Conversational Analysis
EmotionAI presents a locally-run computational pipeline that analyzes speech emotion recognition without uploading sensitive audio to cloud services, combining ASR, speaker diarization, and LLM reasoning. While the system achieves 48.8% accuracy on emotion classification—above random baselines but below traditional methods—it prioritizes privacy and auditability over state-of-the-art performance, running entirely on CPU with minimal latency.