ISSE is an open-source, cross-platform audio editing tool that allows a user to perform source separation by painting on time-frequency visualizations of sound. The software leverages both a new user interaction paradigm and machine learning-based separation algorithm that "learns" from human feedback (e.g. painting annotations) to perform separation.
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