EmotionSync:AI-Driven Emotion-Aware Recommendation System for Smart Task Prioritization, Well-Being Productivity

What if AI has the ability to sense your emotions in addition to hearing what you say? Emotions are the language of the body, thoughts are the language of the mind, and words are the link between them; they convey sentiment, meaning, and purpose. AI, however, has trouble understanding this synergy; this paper presents Emotion Syn, an AI-powered Emotion-Aware Recommendation System that turns speech into tailored insights. It uses OpenAI Whisper to transcribe speech inputs, Named Entity Recognition (NER) to extract context, and a refined EmoRoBERTa model (93% accuracy) to identify emotions. A RAG based LLM enhances personalization by retrieving relevant knowledge from books, past interactions, and external sources. Transformer models (T5) refine suggestions and Multi-Armed Bandit (MAB) algorithms produce adaptive task and well-being recommendations, dynamically prioritizing schedules through interaction with Google Calendar. The system is a fluid, emotion-aware AI companion that comprehends not just what people say but also how they feel thanks to an ongoing feedback loop that improves ideas. Emotion Syn converts emotional intelligence into action, bridging the gap between wellbeing and productivity.