• Pooja Hansda
• Priya M
• Radhika D
• Sharadhi S Shetty

Across cultures, music plays a vital role in reflecting and shaping human emotions, often transcending language and personal barriers. It has the ability to uplift, comfort, energize and soothe and sometimes all at once. However, in today’s world of music recommendation systems, we are left with suggestions that feel impersonal or disconnected from our current emotional state. This is where Expressify comes in. Expressify is an emotion- based music recommendation system designed to offer a deeply personalized listening experience. By analyzing real-time emotional cues - such as facial expressions, speech tone, and text sentiment. Expressify matches the mood with the perfect music genre and track. Using a curated dataset with emotion-genre associations. Expressify delivers accurate, mood-aligned recommendations, whether you're unwinding or seeking motivation. This innovative approach not only makes music discovery more dynamic but also more meaningful, offering a truly emotional and personalized experience for every listener, highlighting the potential of integrating emotion-aware AI with entertainment platforms to create more engaging and meaningful user interactions.

Deepface, CNN, VaderSentiment, TextBlob, Parselmouth

"EXPRESSIFY: EMOTION-BASED MUSIC RECOMMENDATION SYSTEM ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 7, page no.404-407, July-2025, Available :http://www.jetir.org/papers/JETIRGX06075.pdf

"EXPRESSIFY: EMOTION-BASED MUSIC RECOMMENDATION SYSTEM ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 7, page no. pp404-407, July-2025, Available at : http://www.jetir.org/papers/JETIRGX06075.pdf