EMORA is a multimodal AI conversational agent that integrates text, audio, and visual signals to understand emotion-related patterns. It combines MFN-based emotion recognition, conversational memory, and adaptive response strategies with Llama 3-MAGneT. Built to explore context-aware, supportive conversations for behaviour-change support.
8th Place Solution — DataVerse: Detecting Emotions from Hindi Speech (SRCASW-BhavVaani) | Multimodal Acoustic-Semantic Deep Ensemble (0.9278 OOF / 0.93030 LB)
Fully offline Mandarin speech emotion quantification (Russell V-A, 6-modality fusion) with personalized auditory stimulus generation. Research tool; every method annotated by evidence level and validated on AISHELL-3 / CSEMOTIONS.
语音端到端情绪识别与心理评估报告生成（示例数据为合成记录）
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