Why Computational Audiology ?

The purpose of this online forum is to share knowledge about computational audiology. We hope to bring experts from different disciplines such as AI and Audiology together in order to stimulate innovations for hearing impaired people anywhere. We publish blog articles about current developments, highlight ongoing projects and publications by research groups, and aim to facilitate discussion. In addition, the website is used to promote events related to computational audiology.

Anybody can leave a comment or share content to publish on the forum, after providing a name and valid email address. Comments only appear on the website after approval by the moderators.​ Content can be rejected if it is not within the scope of the forum or considered disrespectful. The tone of the forum is respectful and pleasantly informal.

What is computational audiology?

Computational audiology is the augmentation of traditional hearing health care by digital methods including artificial intelligence and machine learning. Continue reading

News & Agenda

Donders Institute and Radboud University open of a third ICAI lab.

The AI for Neurotech Lab aims to develop machine learning solutions for brain reading and writing, to restore sensory and cognitive functions. These solutions could include hearing tools for the deaf ...

Research Topic: Digital Hearing Healthcare

The Frontiers Research Topic “Digital Hearing Healthcare,” edited by Qinglin Meng, Jing Chen, Changxin Zhang, Dennis Barbour and Fan-Gang Zeng, is now open for submissions.

VCCA2020 on-demand

Register now to get access to the on-demand version of the VCCA2020 conference. A clean version of all recordings is available until November 1.

Blogs and project about computational audiology

Below you find blogs about computational audiology, but also featured talks, and presentations of on-going projects submitted for the VCCA2020 conference. An overview of the VCCA2020 conference program is provided here. Further backgrounds can be the virtual goodiebag.  

The biggest hurdle facing computational audiologists may not be perfecting machine learning methods, but creating the infrastructure- including hardware, data
Remote Audiology Delivery Care COVID-19
Modeling speech perception in hidden hearing loss using stochastically undersampled neuronal firing patterns
Speech perception by hearing aid (HA) users has been evaluated in a database that includes up to 45 hours of
The U.S. National Hearing Test has now been taken by over 150,000 people and this extensive database provides reliable estimates
PTA is more enlightening than speech-ABR to predict aided behavioural measures.
Detection of current shunts with a ladder-network model
Test-retest analysis of aggregated audiometry testing data using Jacoti Hearing Center self-testing application
Towards the development of a diagnostic supporting tool in audiology, the Common Audiological Functional Parameters (CAFPAs) were shown to be
Applying biophysical auditory periphery models for real-time applications and studies of hearing impairment