Maestro, the music platform that makes it effortless to find songs in new genres.
https://maestro-six.vercel.app
This was a project for CSCE 445 - Computers and New Media with Dr. Frank Shipman at Texas A&M University. Needless to say, it's not as robust as we would have liked it.
Our inital goal was to create a web application that suggested classical pieces based on a user’s individual music preferences - however, we broadened this scope to encompass all available genres on Spotify.
- Acquire playlist information
- Analyze quantitative characteristics (mood, tempo, danceability, timbre, etc.) of songs in playlist
- Provide classical recommendations based on an assessment of the playlist’s musical qualities
- Media Issues
- Will the viewer be able to stream music from our platform?
- Will we be able to create a successful recommendation model with given datasets and tools/API’s? (Spotify, etc)
- Are there parameters that skew results?
- Cognitive Issues
- Do the recommendations make sense?
- Are the results displayed in an effective manner?
- Will the recommendations be useful to user? (feedback)
- Social Issues
- Are there vulnerabilities that can allow for interference by other people?
- Are users willing to share their playlist information?
- Is user information secure (account info)?
Me: Frontend developer for user interface design, API integration
Matthew DeLorenzo: Backend data processing (music qualities, analysis)
Brian Chen: Backend developer
Ken Guo: Backend developer