The effect of masker type and cochlear implant speech processing strategy on speech intelligibility is investigated with typical-hearing listeners using vocoding as a simulation of cochlear implant processing.
ChatGPT can support hearing self-monitoring by providing expert-level recommendations based on mobile app data.
Monitoring cortical responses via fNIRS in a child with bimodal hearing transitioning to bilateral cochlear implants revealed significant adaptation to the second implant and highlighted the potential of this technology to monitor auditory brain development in this population, including the importance of measuring rehabilitation outcomes.
Machine learning models trained on simulated auditory nerve representations demonstrate the limits of attentional selection of speech in cocktail party scenario when heard through a cochlear implant.
A computational model of the stimulated peripheral auditory system shows that the focused partial‑tripolar versus monopolar threshold difference could be a possible indicator of neural health status. Additionally, the model incorporates a novel intracranial auditory prosthesis, revealing that it elicits lower stimulation thresholds and distinct activation patterns compared to conventional cochlear implants.
This project explores the use of Automatic Speech Recognition (ASR) models to transcribe and score open-set speech audiometry responses from cochlear implant users, demonstrating that ASR models can approximate benchmark scores while significantly reducing transcription time.
The current study employs stimuli that are reconstructed by vocoding stimulation patterns generated by an actual CI, then presented to NH listeners to determine psychometric curves for VTL difference.
A computational model that simulates loudness perception experiments using a peripheral auditory model for electric and acoustic stimulation (PAMEAS).
This study introduces a new method for designing optimized multipolar stimulation strategies, offering improved auditory perception with potentially reduced energy consumption.
A lightweight adversarially trained end-to-end model improves speech clarity for cochlear implant users in noisy environments without increasing system complexity.
This study compares cochlear implant processing strategies and finds that the HSSE method preserves both spectral and envelope cues in a balanced way, making it most similar to natural sound.
This project aims to assess the impact of reverberation on spatial acuity by measuring the minimum audible angle (MAA) in child and young adult bilateral cochlear implant users in simulated reverberant environments.
Typical hearing participants show perceptual learning but not sensorimotor learning with real-time noise vocoded speech auditory feedback during speech production.
We have designed and are trialling Virtual Reality games to help children with bilateral cochlear implants hear better.
Vocal emotion recognition in children with hearing aids and children with cochlear implants improves across childhood and adolescence, albeit at a seemingly slower pace compared to children with normal hearing.
Children with single-sided deafness and a cochlear implant (CI) can perceive and use voice cues with their CI, although they do so with less accuracy than children with bilateral CIs.
The Oticon Medical Field Research Platform is an iOS app allowing for real-time monitoring of CI users' daily experiences.
Deep neural network models with altered input clarify the role of plasticity in cochlear implant users’ hearing difficulties.
Coping with noise and reverberation using multi-channel speech enhancement DNN algorithms for cochlear implants
Characterizing the representation of vocal tract length differences in the output signal of cochlear implants.
By selectively altering spectral and temporal F0 cues, we study their contributions to CI pitch perception in real sounds.
Video game with vibrotactile feedback for musical training of children with Cochlear Implants and Auditory Nerve deficiency.
A “hilltop” approach for maximising loudness and minimising channel interactions in Cochlear Implant users