VibeSync-Mood Based Song Recommendation System

Abstract

VibeSync is an AI-powered music recommendation
system that suggests songs based on the user's
current mood, identified through facial expression
analysis. The system uses computer vision and
machine learning techniques to detect emotions such
as happiness, sadness, anger, and neutrality by
analyzing real-time input from the user's webcam.
These emotional states are mapped to mood
categories, which are then used to generate
customized song recommendations from a
predefined music database.
VibeSync features a user-friendly interface that
displays the detected mood and provides relevant
song suggestions instantly. Unlike traditional
recommendation systems that rely on user input or
listening history, VibeSync responds to real-time
emotional cues, offering a more dynamic and
personalized listening experience.
This project showcases the effective integration of
facial expression detection, emotion classification,
and multimedia processing. It demonstrates how
artificial intelligence can be used to create
emotionally intelligent applications that enhance
user engagement, promote mental wellness, and
personalize digital experiences.