61 citations · 277 across the 41 of their papers we have counts for
4 papers · 2 filters
Employing Real Training Data for Deep Noise Suppression
Ziyi Xu, Marvin Sach, Jan Pirklbauer +1
Most deep noise suppression (DNS) models are trained with reference-based losses requiring access to clean speech. However, sometimes an additive microphone model is insufficient f…
Efficient Acoustic Echo Suppression with Condition-Aware Training
Ernst Seidel, Pejman Mowlaee, Tim Fingscheidt
The topic of deep acoustic echo control (DAEC) has seen many approaches with various model topologies in recent years. Convolutional recurrent networks (CRNs), consisting of a conv…
EffCRN: An Efficient Convolutional Recurrent Network for High-Performance Speech Enhancement
Marvin Sach, Jan Franzen, Bruno Defraene +4
Fully convolutional recurrent neural networks (FCRNs) have shown state-of-the-art performance in single-channel speech enhancement. However, the number of parameters and the FLOPs/…
Coded Speech Quality Measurement by a Non-Intrusive PESQ-DNN
Ziyi Xu, Ziyue Zhao, Tim Fingscheidt
Wideband codecs such as AMR-WB or EVS are widely used in (mobile) speech communication. Evaluation of coded speech quality is often performed subjectively by an absolute category r…