257 citations · 969 across the 53 of their papers we have counts for
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cs.SD2017★ 1 cited
Normalized Features for Improving the Generalization of DNN Based Speech Enhancement
Robert Rehr, Timo Gerkmann
Enhancing noisy speech is an important task to restore its quality and to improve its intelligibility. In traditional non-machine-learning (ML) based approaches the parameters requ…
cs.SD2017★ 31 cited
DNN and CNN with Weighted and Multi-task Loss Functions for Audio Event Detection
Huy Phan, Martin Krawczyk-Becker, Timo Gerkmann +1
This report presents our audio event detection system submitted for Task 2, "Detection of rare sound events", of DCASE 2017 challenge. The proposed system is based on convolutional…
cs.SD2017★ 23 cited
On the Importance of Super-Gaussian Speech Priors for Machine-Learning Based Speech Enhancement
Robert Rehr, Timo Gerkmann
For enhancing noisy signals, machine-learning based single-channel speech enhancement schemes exploit prior knowledge about typical speech spectral structures. To ensure a good gen…