Moodify: Personalized Music Recommendations Based on Your Mood

Project Overview

Moodify is an innovative music app designed to recommend songs that match users' current emotional states. By leveraging creative mood detection techniques and interactive features, the app delivers a deeply personalized listening experience that resonates with users on a whole new level.

Key Features

• Creative Mood Detection
  Users can input their mood via text, select colors or images, or hum/sing into the microphone. Advanced sentiment analysis and audio processing power the mood detection engine.

• Dynamic Music Recommendations
  Moodify curates playlists that evolve with users’ emotional transitions, providing a seamless, mood-adaptive music experience.

• Mood Diary & Tracking
  Track mood patterns over time to tailor long-term music suggestions aligned with user wellbeing.

Technologies Used

• Frontend: Next.js
  
• Backend: NestJS
  
• Music & AI: OpenAI API (for sentiment analysis and music recommendation)
  
• Database: PostgreSQL
  
• Storage: AWS S3 (for images, audio samples, etc.)
  
• Deployment: Vercel (frontend)

Hackathon Focus

• Real-time mood detection from text, images, and humming input
  
• Adaptive playlist generation reflecting mood transitions
  
• User mood diary visualization
  

Tagline

"Feel the Mood, Hear the Tune."

Built With

• aws3
• nest
• next
• openai
• postgresql
• react
• vercel