97 citations · 336 across the 30 of their papers we have counts for
12 papers · 1 filter
Training Set Synthesis for Bioacoustic Denoising: A Case Study With Mice
Reyhaneh Abbasi, Peter Balazs, Vincent Lostanlen +4
Bioacoustic recordings are often degraded by ambient noise, which complicates the analysis of weak or noise-overlapped vocalizations. Convolutional neural networks, particularly U-…
ISAC: An Invertible and Stable Auditory Filter Bank with Customizable Kernels for ML Integration
Daniel Haider, Felix Perfler, Peter Balazs +2
This paper introduces ISAC, an invertible and stable, perceptually-motivated filter bank that is specifically designed to be integrated into machine learning paradigms. More precis…
Non-iterative Filter Bank Phase (Re)Construction
Zdeněk Průša, Nicki Holighaus
Signal reconstruction from magnitude-only measurements presents a long-standing problem in signal processing. In this contribution, we propose a phase (re)construction method for f…
Phase-Based Signal Representations for Scattering
Daniel Haider, Peter Balazs, Nicki Holighaus
The scattering transform is a non-linear signal representation method based on cascaded wavelet transform magnitudes. In this paper we introduce phase scattering, a novel approach…
Audio Inpainting via -Minimization and Dictionary Learning
Shristi Rajbamshi, Georg Tauböck, Peter Balazs +1
Audio inpainting refers to signal processing techniques that aim at restoring missing or corrupted consecutive samples in audio signals. Prior works have shown that - minim…
Phase Vocoder Done Right
Zdenek Prusa, Nicki Holighaus
The phase vocoder (PV) is a widely spread technique for processing audio signals. It employs a short-time Fourier transform (STFT) analysis-modify-synthesis loop and is typically u…
GACELA -- A generative adversarial context encoder for long audio inpainting
Andres Marafioti, Piotr Majdak, Nicki Holighaus +1
We introduce GACELA, a generative adversarial network (GAN) designed to restore missing musical audio data with a duration ranging between hundreds of milliseconds to a few seconds…
Adversarial Generation of Time-Frequency Features with application in audio synthesis
Andrés Marafioti, Nicki Holighaus, Nathanaël Perraudin +1
Time-frequency (TF) representations provide powerful and intuitive features for the analysis of time series such as audio. But still, generative modeling of audio in the TF domain…
Audio inpainting of music by means of neural networks
Andrés Marafioti, Nicki Holighaus, Piotr Majdak +1
We studied the ability of deep neural networks (DNNs) to restore missing audio content based on its context, a process usually referred to as audio inpainting. We focused on gaps i…
Frame Theory for Signal Processing in Psychoacoustics
Peter Balazs, Nicki Holighaus, Thibaud Necciari +1
This review chapter aims to strengthen the link between frame theory and signal processing tasks in psychoacoustics. On the one side, the basic concepts of frame theory are present…
Inpainting of long audio segments with similarity graphs
Nathanael Perraudin, Nicki Holighaus, Piotr Majdak +1
We present a novel method for the compensation of long duration data loss in audio signals, in particular music. The concealment of such signal defects is based on a graph that enc…
A Perceptually Motivated Filter Bank with Perfect Reconstruction for Audio Signal Processing
Thibaud Necciari, Nicki Holighaus, Peter Balazs +1
Many audio applications rely on filter banks (FBs) to analyze, process, and re-synthesize sounds. To approximate the auditory frequency resolution in the signal chain, some applica…