Using AI for music source separation - Lee, Jasline Jie Yu (Nanyang Technological University, 2021)
This report summarizes the research, methodologies, and experimental implementation on Music Source Separation (MSS). It is the task of isolating individual instrument source signals that we are interested in from a music piece. In recent years, supervised deep learning methods are known to be state-of-the-art source separation technology and can be categorised as Spectrogram-based and Waveform-based methods. These models usually run on large computational power across multiple GPUs over long training hours. Albeit the success of integrating machine learning in the separation process, many lack visual representation for users to appreciate the connection between the input, model, and output.