prof. dr. Sarah Verhulst
- Work address
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Technologiepark Zwijnaarde 126
9052 Zwijnaarde - sarah.verhulst@ugent.be
- ORCID iD
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0000-0002-6498-7719
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- Journal Article
- open access
Predicting synapse counts in living humans by combining computational models with auditory physiology
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Learning from model-based approaches for hearing lLoss compensation: which speech features are enhanced in machine-learning-based audio algorithms for cochlear synaptopathy compensation?
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- Conference Paper
- C1
- open access
A differentiable optimisation framework for the design of individualised DNN-based hearing-aid strategies
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- Conference Paper
- C3
- open access
Speech intelligibility in tinnitus and ageing : exploring the role of impaired peripheral and brainstem processing
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Cochlear synaptopathy in the ageing population
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Biophysically realistic neural-network models of auditory neurons and synapses for neuroscience and machine-hearing applications
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Individualized cochlear models based on distortion product otoacoustic emissions
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- Journal Article
- A1
- open access
The variability in potential biomarkers for cochlear synaptopathy after recreational noise exposure
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- Journal Article
- A1
- open access
A convolutional neural-network framework for modelling auditory sensory cells and synapses
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Test-retest reliability of auditory-evoked potentials