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This project aims at filtering out the human vocals of songs using a library Spleeter, and turning them into instrumental versions, creating an ideal platform for young talented music enthusiasts to explore and learn to play various instruments. The vocals are converted to covers using the Differentiable Digital Signal Processing (DDSP) library, which enables direct integration of signal processing elements with deep learning techniques.
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Currently in the music industry, after recording original songs with lyrics, they are re-recorded for covers. AInstrument can also help music professionals and artists in turning existing songs to a particular instrumental cover to suit their need and also allows them to release various versions of their songs, without the burden of extra effort and money.
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Web Frontend developed using Angular
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Backend developed using Flask
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DDSP: Differentiable Digital Signal Processing
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Spleeter
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Data stored in Firebase
- User Authenication using Firebase
- Separation of the human vocals from the lyrical songs.
- Conversion of the song into various instrumental covers with differently tuned parameters to provide the end users with various options.
- Figuring out the notes from the converted instrumental cover.
- Very robust and high fidelity audio synthesis system.
- This system will remove the dependency of the instrument learning process of callow students on musicians.
