Techn. Fakultät Website deprecated and outdated. Click here for the new site. FAU-Logo

Hendrik Schröter M. Sc.

Researcher in the Speech Processing and Understanding (SAGI) group at the Pattern Recognition Lab of the Friedrich-Alexander-Universität Erlangen-Nürnberg

Deep Learning based Noise Reduction for Hearing Aids


Reduction of unwanted environmental noises is an important feature of today’s hearing aids, which is why noise reduction is nowadays included in almost every commercially available device. The majority of these algorithms, however, is restricted to the reduction of stationary noises. Due to the large number of different background noises in daily situations, it is hard to heuristically cover the complete solution space of noise reduction schemes. Deep learning-based algorithms pose a possible solution to this dilemma, however, they sometimes lack robustness and applicability in the strict context of hearing aids.
In this project we investigate several deep learning based methods for noise reduction under the constraints of modern hearing aids. This involves a low latency processing as well as the employing a hearing instrument-grade filter bank. Another important aim is the robustness of the developed methods. Therefore, the methods will be applied to real-world noise signals recorded with hearing instruments.