18 citations · 19 across the 6 of their papers we have counts for
7 papers
Real-time multichannel deep speech enhancement in hearing aids: Comparing monaural and binaural processing in complex acoustic scenarios
Nils L. Westhausen, Hendrik Kayser, Theresa Jansen +1
Deep learning has the potential to enhance speech signals and increase their intelligibility for users of hearing aids. Deep models suited for real-world application should feature…
Binaural multichannel blind speaker separation with a causal low-latency and low-complexity approach
Nils L. Westhausen, Bernd T. Meyer
In this paper, we introduce a causal low-latency low-complexity approach for binaural multichannel blind speaker separation in noisy reverberant conditions. The model, referred to…
Low bit rate binaural link for improved ultra low-latency low-complexity multichannel speech enhancement in Hearing Aids
Nils L. Westhausen, Bernd T. Meyer
Speech enhancement in hearing aids is a challenging task since the hardware limits the number of possible operations and the latency needs to be in the range of only a few millisec…
tPLCnet: Real-time Deep Packet Loss Concealment in the Time Domain Using a Short Temporal Context
Nils L. Westhausen, Bernd T. Meyer
This paper introduces a real-time time-domain packet loss concealment (PLC) neural-network (tPLCnet). It efficiently predicts lost frames from a short context buffer in a sequence-…
Reduction of Subjective Listening Effort for TV Broadcast Signals with Recurrent Neural Networks
Nils L. Westhausen, Rainer Huber, Hannah Baumgartner +3
Listening to the audio of TV broadcast signals can be challenging for hearing-impaired as well as normal-hearing listeners, especially when background sounds are prominent or too l…
Acoustic echo cancellation with the dual-signal transformation LSTM network
Nils L. Westhausen, Bernd T. Meyer
This paper applies the dual-signal transformation LSTM network (DTLN) to the task of real-time acoustic echo cancellation (AEC). The DTLN combines a short-time Fourier transformati…
Dual-Signal Transformation LSTM Network for Real-Time Noise Suppression
Nils L. Westhausen, Bernd T. Meyer
This paper introduces a dual-signal transformation LSTM network (DTLN) for real-time speech enhancement as part of the Deep Noise Suppression Challenge (DNS-Challenge). This approa…