Ethan Manilow, Prem Seetharaman, Fatemeh Pishdadian, Bryan Pardo
This work was supported by National Science Foundation Award 1420971
The Northwestern University Source Separation Library (nussl) provides implementations of common audio source separation algorithms as well as an easy-to-use framework for prototyping and adding new algorithms.
Audio source separation is the process of isolating individual sonic elements from a mixture or auditory scene. Nussl is an open-source, object-oriented audio source separation library implemented in Python. nussl provides implementations for many existing source separation algorithms and a platform for creating the next generation of source separation algorithms. By nature of its design, nussl easily allows new algorithms to be benchmarked against existing algorithms on established data sets and facilitates development of new variations on algorithms.
The aim of nussl is to create a low barrier to entry for using popular source separation algorithms, while also allowing the user fine tuned control of low-level parameters.
[pdf] E. Manilow, P. Seetharaman, and B. Pardo, “The Northwestern University Source Separation Library,” in Proceedings of the 19th International Society of Music Information Retrieval Conference (ISMIR 2018), 2018.