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Found 7 papers, 4 papers with code
AMT 1.x: A toolbox for reproducible research in auditory modeling
The AMT aims for a consistent implementation of auditory models, well-structured in-code documentation, and inclusion of auditory data required to run the models.
A comparative study of eight human auditory models of monaural processing
A number of auditory models have been developed using diverging approaches, either physiological or perceptual, but they share comparable stages of signal processing, as they are inspired by the same constitutive parts of the auditory system.
Time-Frequency Phase Retrieval for Audio -- The Effect of Transform Parameters
To address this, we studied the performance of three PR algorithms for various types of audio content and various STFT parameters such as redundancy, time-frequency ratio, and the type of window.
GACELA -- A generative adversarial context encoder for long audio inpainting
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, i. e., to perform long-gap audio inpainting.
Adversarial Generation of Time-Frequency Features with application in audio synthesis
We demonstrate the potential of deliberate generative TF modeling by training a generative adversarial network (GAN) on short-time Fourier features.
Audio inpainting of music by means of neural networks
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.
Inpainting of long audio segments with similarity graphs
We present a novel method for the compensation of long duration data loss in audio signals, in particular music.
