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Spotify Mood AR

Spotify Mood AR
Year
2022
Stack
Python, Flask, TensorFlow, OpenCV, Figma

Description

Spotify Mood AR is an experimental augmented reality web app that recommends music based on real-time facial emotion recognition. Using a webcam, the app detects the user's emotional expression and suggests a Spotify track that aligns with their current mood. Users can even change the recommended song by covering their face, triggering a new emotion detection cycle.

My role

I contributed to this project by exploring the intersection of machine learning, computer vision, and music APIs. I worked with pre-trained emotion detection models, integrated the system into a Flask web app, and designed the interface using Figma to ensure a simple, responsive experience. I also helped implement interaction with the Spotify API for music recommendations.

The result

The result is a functional prototype that showcases the potential of combining AI-driven emotion analysis with music personalization. While still in the experimental stage, the app demonstrates innovative use of AR and provides a foundation for future development into real-world, emotion-based music applications.