Biomimetic Cochlear Implant Coding: A Strategy Employing a Cochlear Model and Deep Neural Network
ChatGPT can support hearing self-monitoring by providing expert-level recommendations based on mobile app data.
Cortical benefits of DNN-based noise management in experienced hearing aid users measured using functional near infrared spectroscopy (fNIRS)
This study used functional near-infrared spectroscopy to show that a deep neural network-based noise management program in hearing aids reduced listening effort and brain activation in the left prefrontal cortex over a traditional quiet-listening program while in a lab-controlled noisy environment.
Recovering speech intelligibility for cochlear implants in noisy and reverberant situations using multi-microphone deep learning algorithms
Coping with noise and reverberation using multi-channel speech enhancement DNN algorithms for cochlear implants
IndivHear: An Individualized Adaptive Deep Learning-Based Hearing Aid
IndivHear is a deep reinforcement-learning-based hearing aid focussed on the complex nature of individual hearing losses
Having choices for enhancing voices: Target speaker extraction in noisy multi-talker environments using deep neural networks
Target speaker-informed speech enhancement approaches can enhance speech perception in noisy multi-talker environments
A WaveNet-based cochlear filtering and hair cell transduction model for applications in speech and music processing
WaveNet-based auditory model approximation is accurate, computationally efficient, and differentiable.