Deep Learning based Noise Reduction for Hearing Aids

Deep Learning based Noise Reduction for Hearing Aids

(Third Party Funds Single)

Overall project:
Project leader:
Project members: ,
Start date: February 1, 2019
End date: January 31, 2022
Funding source: Industrie



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