51 citations · 168 across the 23 of their papers we have counts for
23 papers
Audio Inpainting in Time-Frequency Domain with Phase-Aware Prior
Peter Balušík, Pavel Rajmic
We address the problem of time-frequency audio inpainting, where the goal is to fill missing spectrogram portions with consistent information. Despite recent advances, existing app…
A MATLAB toolbox for Computation of Speech Transmission Index (STI)
Pavel Rajmic, Jiří Schimmel, Šimon Cieslar
The speech transmission index (STI) is a popular simple metric for the prediction of speech intelligibility when speech is passed through a transmission channel. Computation of STI…
Audio dequantization using instantaneous frequency
Vojtěch Kovanda, Pavel Rajmic
We present a dequantization method that employs a phase-aware regularizer, originally successfully applied in an audio inpainting problem. The method promotes a temporal continuity…
Dequantization of a signal from two parallel quantized observations
Vojtěch Kovanda, Pavel Rajmic
We propose a technique of signal acquisition using a combination of two devices with different sampling rates and quantization accuracies. Subsequent processing involving sparsity…
Janssen 2.0: Audio Inpainting in the Time-frequency Domain
Ondřej Mokrý, Peter Balušík, Pavel Rajmic
The paper focuses on inpainting missing parts of an audio signal spectrogram, i.e., estimating the lacking time-frequency coefficients. The autoregression-based Janssen algorithm,…
Tweaking autoregressive methods for inpainting of gaps in audio signals
Ondřej Mokrý, Pavel Rajmic
A novel variant of the Janssen method for audio inpainting is presented and compared to other popular audio inpainting methods based on autoregressive (AR) modeling. Both conceptua…
Improving DCE-MRI through unfolded low-rank + sparse optimisation
Ondřej Mokrý, Jiří Vitouš, Pavel Rajmic +1
A method for perfusion imaging with DCE-MRI is developed based on two popular paradigms: the low-rank + sparse model for optimisation-based reconstruction, and the deep unfolding.…
Multiple Hankel matrix rank minimization for audio inpainting
Pavel Záviška, Pavel Rajmic, Ondřej Mokrý
Sasaki et al. (2018) presented an efficient audio declipping algorithm, based on the properties of Hankel-structure matrices constructed from time-domain signal blocks. We adapt th…
Audio Declipping with (Weighted) Analysis Social Sparsity
Pavel Záviška, Pavel Rajmic
We develop the analysis (cosparse) variant of the popular audio declipping algorithm of Siedenburg et al. (2014). Furthermore, we extend both the old and the new variants by the po…
Audio declipping performance enhancement via crossfading
Pavel Záviška, Pavel Rajmic, Ondřej Mokrý
Some audio declipping methods produce waveforms that do not fully respect the physical process of clipping, which is why we refer to them as inconsistent. This letter reports what…
Audio Dequantization Using (Co)Sparse (Non)Convex Methods
Pavel Záviška, Pavel Rajmic, Ondřej Mokrý
The paper deals with the hitherto neglected topic of audio dequantization. It reviews the state-of-the-art sparsity-based approaches and proposes several new methods. Convex as wel…
A survey and an extensive evaluation of popular audio declipping methods
Pavel Záviška, Pavel Rajmic, Alexey Ozerov +1
Dynamic range limitations in signal processing often lead to clipping, or saturation, in signals. The task of audio declipping is estimating the original audio signal, given its cl…
Approximal operator with application to audio inpainting
Ondřej Mokrý, Pavel Rajmic
In their recent evaluation of time-frequency representations and structured sparsity approaches to audio inpainting, Lieb and Stark (2018) have used a particular mapping as a proxi…
Flexible framework for audio reconstruction
Ondřej Mokrý, Pavel Rajmic, Pavel Záviška
The paper presents a unified, flexible framework for the tasks of audio inpainting, declipping, and dequantization. The concept is further extended to cover analogous degradation m…
Sparse and Cosparse Audio Dequantization Using Convex Optimization
Pavel Záviška, Pavel Rajmic
The paper shows the potential of sparsity-based methods in restoring quantized signals. Following up on the study of Brauer et al. (IEEE ICASSP 2016), we significantly extend the r…
Audio Inpainting: Revisited and Reweighted
Ondřej Mokrý, Pavel Rajmic
We deal with the problem of sparsity-based audio inpainting, i.e. filling in the missing segments of audio. A consequence of the approaches based on mathematical optimization is th…
Psychoacoustically Motivated Audio Declipping Based on Weighted l1 Minimization
Pavel Záviška, Pavel Rajmic, Jíří Schimmel
A novel method for audio declipping based on sparsity is presented. The method incorporates psychoacoustic information by weighting the transform coefficients in the minim…
Image edges resolved well when using an overcomplete piecewise-polynomial model
Michaela Novosadová, Pavel Rajmic
Used in the paper is an overcomplete piecewise-polynomial image model incorporating sparsity. The paper shows that using such a model, the edges in the image can be resolved robust…
Introducing SPAIN (SParse Audio INpainter)
Ondřej Mokrý, Pavel Záviška, Pavel Rajmic +1
A novel sparsity-based algorithm for audio inpainting is proposed. It is an adaptation of the SPADE algorithm by Kitić et al., originally developed for audio declipping, to the tas…
A Proper version of Synthesis-based Sparse Audio Declipper
Pavel Záviška, Pavel Rajmic, Ondřej Mokrý +1
Methods based on sparse representation have found great use in the recovery of audio signals degraded by clipping. The state of the art in declipping has been achieved by the SPADE…
S-SPADE Done Right: Detailed Study of the Sparse Audio Declipper Algorithms
Pavel Záviška, Ondřej Mokrý, Pavel Rajmic
This technical report shows and discusses in detail how Sparse Audio Declipper (SPADE) algorithms are derived from the signal model using the ADMM approach. The analysis version (A…
Revisiting Synthesis Model of Sparse Audio Declipper
Pavel Záviška, Pavel Rajmic, Zdeněk Průša +1
The state of the art in audio declipping has currently been achieved by SPADE (SParse Audio DEclipper) algorithm by Kitić et al. Until now, the synthesis/sparse variant, S-SPADE, h…
Proceedings of the second "international Traveling Workshop on Interactions between Sparse models and Technology" (iTWIST'14)
L. Jacques, C. De Vleeschouwer, Y. Boursier +64
The implicit objective of the biennial "international - Traveling Workshop on Interactions between Sparse models and Technology" (iTWIST) is to foster collaboration between interna…