186 citations · 275 across the 12 of their papers we have counts for
13 papers
Joint Spectrogram Separation and TDOA Estimation using Optimal Transport
Linda Fabiani, Sebastian J. Schlecht, Isabel Haasler +1
Separating sources is a common challenge in applications such as speech enhancement and telecommunications, where distinguishing between overlapping sounds helps reduce interferenc…
Fade-in Reverberation in Multi-room Environments Using the Common-Slope Model
Kyung Yun Lee, Nils Meyer-Kahlen, Georg Götz +3
In multi-room environments, modelling the sound propagation is complex due to the coupling of rooms and diverse source-receiver positions. A common scenario is when the source and…
Optimizing tiny colorless feedback delay networks
Gloria Dal Santo, Karolina Prawda, Sebastian J. Schlecht +1
A common bane of artificial reverberation algorithms is spectral coloration in the synthesized sound, typically manifesting as metallic ringing, leading to a degradation in the per…
Deep Room Impulse Response Completion
Jackie Lin, Georg Götz, Sebastian J. Schlecht
Rendering immersive spatial audio in virtual reality (VR) and video games demands a fast and accurate generation of room impulse responses (RIRs) to recreate auditory environments…
Damping Density of an Absorptive Shoebox Room Derived from the Image-Source Method
Sebastian J. Schlecht, Karolina Prawda, Rudolf Rabenstein +1
The image-source method is widely applied to compute room impulse responses (RIRs) of shoebox rooms with arbitrary absorption. However, with increasing RIR lengths, the number of i…
Physical Modeling using Recurrent Neural Networks with Fast Convolutional Layers
Julian D. Parker, Sebastian J. Schlecht, Rudolf Rabenstein +1
Discrete-time modeling of acoustic, mechanical and electrical systems is a prominent topic in the musical signal processing literature. Such models are mostly derived by discretizi…
Neural network for multi-exponential sound energy decay analysis
Georg Götz, Ricardo Falcón Pérez, Sebastian J. Schlecht +1
An established model for sound energy decay functions (EDFs) is the superposition of multiple exponentials and a noise term. This work proposes a neural-network-based approach for…
Allpass Feedback Delay Networks
Sebastian J. Schlecht
In the 1960s, Schroeder and Logan introduced delay line-based allpass filters, which are still popular due to their computational efficiency and versatile applicability in artifici…
Scattering in Feedback Delay Networks
Sebastian J. Schlecht, Emanuël A. P. Habets
Feedback delay networks (FDNs) are recursive filters, which are widely used for artificial reverberation and decorrelation. One central challenge in the design of FDNs is the gener…
Modal Decomposition of Feedback Delay Networks
Sebastian J. Schlecht, Emanuël A. P. Habets
Feedback delay networks (FDNs) belong to a general class of recursive filters which are widely used in sound synthesis and physical modeling applications. We present a numerical te…
Automatic Liver and Tumor Segmentation of CT and MRI Volumes using Cascaded Fully Convolutional Neural Networks
Patrick Ferdinand Christ, Florian Ettlinger, Felix Grün +17
Automatic segmentation of the liver and hepatic lesions is an important step towards deriving quantitative biomarkers for accurate clinical diagnosis and computer-aided decision su…
SurvivalNet: Predicting patient survival from diffusion weighted magnetic resonance images using cascaded fully convolutional and 3D convolutional neural networks
Patrick Ferdinand Christ, Florian Ettlinger, Georgios Kaissis +7
Automatic non-invasive assessment of hepatocellular carcinoma (HCC) malignancy has the potential to substantially enhance tumor treatment strategies for HCC patients. In this work…
On Lossless Feedback Delay Networks
Sebastian J. Schlecht, Emanuel A. P. Habets
Lossless Feedback Delay Networks (FDNs) are commonly used as a design prototype for artificial reverberation algorithms. The lossless property is dependent on the feedback matrix,…