62 citations · 139 across the 6 of their papers we have counts for
6 papers
Short-wave admittance correction for a time-domain cochlear transmission line model
François Deloche, Morgan Thienpont, Sarah Verhulst
Transmission line (TL) models implemented in the time domain can efficiently simulate basilar-membrane (BM) displacement in response to transient or non-stationary sounds. By desig…
A Neural-Network Framework for the Design of Individualised Hearing-Loss Compensation
Fotios Drakopoulos, Sarah Verhulst
Sound processing in the human auditory system is complex and highly non-linear, whereas hearing aids (HAs) still rely on simplified descriptions of auditory processing or hearing l…
A comparative study of eight human auditory models of monaural processing
Alejandro Osses Vecchi, Léo Varnet, Laurel H. Carney +4
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 i…
A convolutional neural-network model of human cochlear mechanics and filter tuning for real-time applications
Deepak Baby, Arthur Van Den Broucke, Sarah Verhulst
Auditory models are commonly used as feature extractors for automatic speech-recognition systems or as front-ends for robotics, machine-hearing and hearing-aid applications. Althou…
Calibration and reference simulations for the auditory periphery model of Verhulst et al. 2018 version 1.2
Alejandro Osses Vecchi, Sarah Verhulst
This document describes a comprehensive procedure of how the biophysical model published by Verhulst et al. (2018) can be calibrated on the basis of reference auditory brainstem re…
Machines hear better when they have ears
Deepak Baby, Sarah Verhulst
Deep-neural-network (DNN) based noise suppression systems yield significant improvements over conventional approaches such as spectral subtraction and non-negative matrix factoriza…