148 citations · 497 across the 45 of their papers we have counts for
48 papers
End-To-End Deep Learning-based Adaptation Control for Linear Acoustic Echo Cancellation
Thomas Haubner, Andreas Brendel, Walter Kellermann
The attenuation of acoustic loudspeaker echoes remains to be one of the open challenges to achieve pleasant full-duplex hands free speech communication. In many modern signal enhan…
Airborne Sound Analysis for the Detection of Bearing Faults in Railway Vehicles with Real-World Data
Matthias Kreuzer, David Schmidt, Simon Wokusch +1
In this paper, we address the challenging problem of detecting bearing faults in railway vehicles by analyzing acoustic signals recorded during regular operation. For this, we intr…
1-D Residual Convolutional Neural Network coupled with Data Augmentation and Regularization for the ICPHM 2023 Data Challenge
Matthias Kreuzer, Walter Kellermann
In this article, we present our contribution to the ICPHM 2023 Data Challenge on Industrial Systems' Health Monitoring using Vibration Analysis. For the task of classifying sun gea…
Novel features for the detection of bearing faults in railway vehicles
Matthias Kreuzer, Alexander Schmidt, Walter Kellermann
{In this paper, we address the challenging problem of detecting bearing faults from vibration signals. For this, several time- and frequency-domain features have been proposed alre…
Localizing Spatial Information in Neural Spatiospectral Filters
Annika Briegleb, Thomas Haubner, Vasileios Belagiannis +1
Beamforming for multichannel speech enhancement relies on the estimation of spatial characteristics of the acoustic scene. In its simplest form, the delay-and-sum beamformer (DSB)…
Exploiting spatial information with the informed complex-valued spatial autoencoder for target speaker extraction
Annika Briegleb, Mhd Modar Halimeh, Walter Kellermann
In conventional multichannel audio signal enhancement, spatial and spectral filtering are often performed sequentially. In contrast, it has been shown that for neural spatial filte…