Demo: Live Music Recognition
The Live Music Recognition App is a web application built using the MERN stack (MongoDB, Express.js, React, Node.js). It integrates two powerful APIs:
- Spotify API: To fetch similar songs and detailed music metadata.
- ACRCloud API: To recognize music playing in the environment.
This app allows users to identify music playing nearby and discover similar tracks using Spotify.
- Music Recognition: Recognize songs in real time using ACRCloud.
- Similar Tracks: Fetch similar tracks and metadata from Spotify.
- User-Friendly Interface: Intuitive design for seamless user experience.
- Cross-Platform Support: Accessible on both desktop and mobile devices.
- React: For building the user interface.
- CSS/Styled Components: For styling.
- Node.js & Express.js: For creating the API endpoints.
- MongoDB: For storing user preferences or app data.
- Spotify API: To fetch details and suggestions for similar music.
- ACRCloud API: For identifying songs playing in real time.
- Frontend: Vercel
- Backend: Hosted on a cloud server
- Node.js (v14+)
- MongoDB
- Spotify Developer Account
- ACRCloud Account
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Clone the repository:
git clone https://github.com/your-username/live-music-recognition.git cd live-music-recognition -
Install dependencies:
cd client npm install cd ../server npm install
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Configure environment variables: Create a
.envfile in theserverdirectory with the following keys:SPOTIFY_CLIENT_ID=your_spotify_client_id SPOTIFY_CLIENT_SECRET=your_spotify_client_secret ACR_CLOUD_ACCESS_KEY=your_acrcloud_access_key ACR_CLOUD_SECRET_KEY=your_acrcloud_secret_key MONGO_URI=your_mongo_database_uri
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Run the backend server:
cd server npm start -
Run the frontend:
cd client npm start -
Access the application: Open your browser and navigate to
http://localhost:3000.
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Frontend:
- Deployed on Vercel: Ensure the build folder from the React app is uploaded.
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Backend:
- Deploy using cloud services like Heroku, AWS, or any other preferred hosting.
Contributions are welcome! Feel free to open issues or submit pull requests.
This project is licensed under the MIT License.
Enjoy recognizing music effortlessly and exploring similar tracks!