I initially chose MongoDB for its flexibility, but I'm open to exploring SQLite as an alternative. I'll research its JSON capabilities and evaluate its suitability for this project.
254 karma · joined August 1, 2024
Which would be a better alternative?
Using exemplar fingerprints, a representative sample of an artist's music, is a good approach, but success would require detailed fingerprints, a varied dataset, and a well-chosen algorithm.
For artists who change styles, time-series analysis can capture their evolving sound.
The solution will likely need machine learning.
The current solution doesn't use feature hashing or clusterable feature vectors. Instead, it relies on audio fingerprinting, which breaks down short audio samples into unique patterns or "fingerprints" for quick comparison with a large database of known songs.
I agree that the project could definitely use some polishing. I'll prioritize improving the setup instructions and look into adding a file-based DB for flexibility, as well as resolving the npm vulnerabilities. Adding support for directly fingerprinting wav files is a great idea and something I'll prioritize, too.
Regarding the project name, I understand the potential legal implications and will definitely change it. I'd appreciate any suggestions you might have.
I'm excited about the possibility of your contributions. Please, feel free to open a PR whenever you're ready.
Thanks again for your feedback!