# N-HANS: Introducing the Augsburg Neuro-Holistic Audio-eNhancement System

arXiv: https://arxiv.org/abs/1911.07062 · HTML: https://mlsanity.com/paper/1911.07062/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 16 Nov 2019.

## Built on by (most cited first, 1 of 1)

- [Climate Change & Computer Audition: A Call to Action and Overview on Audio Intelligence to Help Save the Planet](https://mlsanity.com/paper/2203.06064/) (2022)

## Abstract (arXiv)

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.