4 citations · 4 across the 2 of their papers we have counts for
2 papers
eess.AS2024★ 4 cited
How to train your ears: Auditory-model emulation for large-dynamic-range inputs and mild-to-severe hearing losses
Peter Leer, Jesper Jensen, Zheng-Hua Tan +2
Advanced auditory models are useful in designing signal-processing algorithms for hearing-loss compensation or speech enhancement. Such auditory models provide rich and detailed de…
cs.SD2023
Dynamic Processing Neural Network Architecture For Hearing Loss Compensation
Szymon Drgas, Lars Bramsløw, Archontis Politis +2
This paper proposes neural networks for compensating sensorineural hearing loss. The aim of the hearing loss compensation task is to transform a speech signal to increase speech in…