  N-HANS is a Python toolkit for in-the-wild audio enhancement, including
speech, music, and general audio denoising, separation, and selective noise or
source suppression. The functionalities are realised based on two neural
network models sharing the same architecture, but trained separately. The
models are comprised of stacks of residual blocks, each conditioned on
additional speech or environmental noise recordings for adapting to different
unseen speakers or environments in real life. In addition to a Python API, a
command line interface is provided to researchers and developers, both of which
are documented at https://github.com/N-HANS/N-HANS. Experimental results
indicate that N-HANS achieves outstanding performance, and ensure its reliable
usage in real-life audio and speech-related tasks, reaching very high audio and
speech quality.
