A new virtual reality-based fine-tuning procedure has been developed for hearing devices, which has the potential to improve the hearing device fit in various real-world scenarios, as suggested by preliminary results from a small study involving cochlear-implant users.
The Oticon Medical Field Research Platform is an iOS app allowing for real-time monitoring of CI users' daily experiences.
Using the Acoustic Change Complex (ACC) prediction model to predict speech perception in noise
Evaluation of the automatic scoring of the DIN test using Kaldi-NL automatic speech recognition with normal-hearing children.
We collected and analyzed hearing aid mic and induction coil input audio recordings from various real-world situations.
Children with listening difficulty have a poorer ability to differentiate target signal from background noise.
Evaluation of HRI via backchannels when normal-hearing adults perform two auditory tests using a NAO humanoid robot.
Improvement of speech in noise comprehension using vibrotactile pulses
mHealth has the potential to deliver scalable hearing health training to ECD practitioners.
Coping with noise and reverberation using multi-channel speech enhancement DNN algorithms for cochlear implants
Datalog: a tool for monitoring the use of amplification devices
We evaluate a measure of individual preferences for noise vs. distortion toward more personalized fine-tuning of hearing aids
The validity of automated smartphone-facilitated in-situ audiometry
Target speaker-informed speech enhancement approaches can enhance speech perception in noisy multi-talker environments
Characterising frequency selectivity changes could provide further insights about the underlying cochlear deficits.
Authors: Amelie Hintermaier1; Iko Pieper1; Tamas Harczos1* 1audifon GmbH & Co. KG Background Hearing aid technology is constantly evolving, resulting in ever more sophisticated algorithms and increasingly powerful hardware. The…
WaveNet-based auditory model approximation is accurate, computationally efficient, and differentiable.
A “hilltop” approach for maximising loudness and minimising channel interactions in Cochlear Implant users
A neural network for diagnosing noise-induced hearing loss from the audioram achieved greater accuracy than existing methods
This study demonstrates reliable and consistent smartphone-based absolute threshold and loudness scaling tests in a home environment
Hearing loss and communication disability questionnaire (HEAR-COMMAND Tool) based on the ICF standard