Explore the words cloud of the RobSpear project. It provides you a very rough idea of what is the project "RobSpear" about.
The following table provides information about the project.
|Coordinator Country||Belgium [BE]|
|Total cost||1˙499˙780 €|
|EC max contribution||1˙499˙780 € (100%)|
1. H2020-EU.1.1. (EXCELLENT SCIENCE - European Research Council (ERC))
|Duration (year-month-day)||from 2016-10-01 to 2021-09-30|
Take a look of project's partnership.
|1||UNIVERSITEIT GENT||BE (GENT)||coordinator||1˙499˙780.00|
|2||CARL VON OSSIETZKY UNIVERSITAET OLDENBURG||DE (OLDENBURG)||participant||0.00|
The prevalence of hearing impairment amongst the elderly is a stunning 33%, while the younger generation is sensitive to noise-induced hearing loss through increasingly loud urban life and lifestyle. Yet, hearing impairment is inadequately diagnosed and treated because we fail to understand how the components that constitute a hearing loss impact robust speech encoding. A recent and ground-breaking discovery in animal physiology demonstrated the existence of a noise-induced hearing deficit -cochlear neuropathy- that coexists with the well-studied cochlear gain loss deficit known to degrade the audibility of sound. Cochlear neuropathy is thought to impact robust encoding of the audible portions of speech and occurs before standard hearing screening methods indicate problems, implying that a large group of noise-exposed people with self-reported hearing problems is currently not screened, nor treated. To design effective hearing restoration strategies, it is crucial to understand how cochlear neuropathy interacts with other hearing deficits to affect robust speech encoding in every-day listening conditions. Through an interdisciplinary approach, RobSpear targets hearing deficits along the ascending stages of the auditory pathway to revolutionize how hearing impairment is diagnosed and treated. RobSpear can yield immense reductions of health care costs through effective treatment of currently misdiagnosed patients and studies the impact of noise-induced hearing deficits on our society. To achieve this, RobSpear: (i) Builds a hearing profile that, based on a computational model of the auditory periphery, develops physiological measures that differentially diagnose hearing deficits in listeners with mixtures of deficits. (ii) Designs individually tailored speech enhancement algorithms that work in adverse conditions and target perceptually relevant speech features, using an unprecedented validation approach that combines novel psychoacoustic and physiological metrics.
|year||authors and title||journal||last update|
Towards a differential diagnosis of cochlear synaptopathy and outer-hair-cell deficits in mixed sensorineural hearing loss pathologies
published pages: , ISSN: , DOI: 10.1101/19008680
The Derived-Band Envelope Following Response and its Sensitivity to Sensorineural Hearing Deficits
published pages: , ISSN: , DOI: 10.1101/820704
Sarah Verhulst, Alessandro AltoÃ¨, Viacheslav Vasilkov
Computational modeling of the human auditory periphery: Auditory-nerve responses, evoked potentials and hearing loss
published pages: 55-75, ISSN: 0378-5955, DOI: 10.1016/j.heares.2017.12.018
|Hearing Research 360||2019-07-08|
Naomi Bramhall, Elizabeth Francis Beach, Bastian Epp, Colleen G. Le Prell, Enrique A. Lopez-Poveda, Christopher J. Plack, Roland Schaette, Sarah Verhulst, Barbara Canlon
The search for noise-induced cochlear synaptopathy in humans: Mission impossible?
published pages: 88-103, ISSN: 0378-5955, DOI: 10.1016/j.heares.2019.02.016
|Hearing Research 377||2019-06-06|
Baby, Deepak; Verhulst, Sarah
Machines hear better when they have ears
published pages: 6, ISSN: , DOI:
Sarah Verhulst, Frauke Ernst, Markus Garrett, Viacheslav Vasilkov
Suprathreshold Psychoacoustics and Envelope-Following Response Relations: Normal-Hearing, Synaptopathy and Cochlear Gain Loss
published pages: 800-803, ISSN: 1610-1928, DOI: 10.3813/aaa.919227
|Acta Acustica united with Acustica 104/5||2019-06-06|
Deepak Baby, Sarah Verhulst
Biophysically-inspired Features Improve the Generalizability of Neural Network-based Speech Enhancement Systems
published pages: 3264-3268, ISSN: , DOI: 10.21437/interspeech.2018-1237
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