Harnessing the power of artificial intelligence to transform hearing healthcare and research
The advances in artificial intelligence that are transforming many fields have yet to make an
impact in hearing. Hearing healthcare continues to rely on a labour-intensive service model …
impact in hearing. Hearing healthcare continues to rely on a labour-intensive service model …
Advanced Artificial Intelligence Algorithms in Cochlear Implants: Review of Healthcare Strategies, Challenges, and Perspectives
Automatic speech recognition (ASR) plays a pivotal role in our daily lives, offering utility not
only for interacting with machines but also for facilitating communication for individuals with …
only for interacting with machines but also for facilitating communication for individuals with …
Deep neural network models of sound localization reveal how perception is adapted to real-world environments
A Francl, JH McDermott - Nature human behaviour, 2022 - nature.com
Mammals localize sounds using information from their two ears. Localization in real-world
conditions is challenging, as echoes provide erroneous information and noises mask parts …
conditions is challenging, as echoes provide erroneous information and noises mask parts …
From microphone to phoneme: an end-to-end computational neural model for predicting speech perception with cochlear implants
Goal: Advances in computational models of biological systems and artificial neural networks
enable rapid virtual prototyping of neuroprostheses, accelerating innovation in the field …
enable rapid virtual prototyping of neuroprostheses, accelerating innovation in the field …
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 …
physiological or perceptual, but they share comparable stages of signal processing, as they …
Neural Mode Estimation
Mode decomposition methods are the current workhorse for the analysis of non-stationary
signals. However, current attempts at these methods mainly focus on improving accuracy …
signals. However, current attempts at these methods mainly focus on improving accuracy …
A neural-network framework for the design of individualised hearing-loss compensation
F Drakopoulos, S Verhulst - IEEE/ACM Transactions on Audio …, 2023 - ieeexplore.ieee.org
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 loss …
hearing aids (HAs) still rely on simplified descriptions of auditory processing or hearing loss …
A convolutional neural-network framework for modelling auditory sensory cells and synapses
In classical computational neuroscience, analytical model descriptions are derived from
neuronal recordings to mimic the underlying biological system. These neuronal models are …
neuronal recordings to mimic the underlying biological system. These neuronal models are …
[HTML][HTML] DNN controlled adaptive front-end for replay attack detection systems
Developing robust countermeasures to protect automatic speaker verification systems
against replay spoofing attacks is a well-recognized challenge. Current approaches to …
against replay spoofing attacks is a well-recognized challenge. Current approaches to …
Predicting the colouration between binaural signals
Although the difference between the fast Fourier transforms of two audio signals is often
used as a basic measure of predicting perceived colouration, these signal measures do not …
used as a basic measure of predicting perceived colouration, these signal measures do not …