Audio Source Separation on Android with Tensorflow 2.0

Audio Source Separation on Android with Tensorflow 2.0

Detailed walkthrough on the complete process of audio source separation with concept, code and functioning app.

Audio source separation is a wonderful use case where every one of us can easily relate with and in this article we are going to deep dive into technical implementations of the solution where we will build an Android app with the TensorFlow model performing audio source separation.

This article will be the first in a two-part series where we will focus on model building activities in the first part, followed by a dedicated article explaining model deployment and data processing on the Android app.

Before getting into the concept, let me tell you we are going to create a faithful reproduction of the Official Spleeter solution in the TF2.0 leveraging its latest features, but for Android use. For those who are not aware, Spleeter is an industry standard audio source separation library and their solution performs at amazing accuracy in splitting the audio into different stems. So, kudos to the authors for building such a wonderful solution.

audio-processing tensorflow-lite audio-source-separation

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