Why Computational Audiology ?

The purpose of this online forum is to share knowledge and tools related to computational audiology. The Computational Audiology Network tries 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. Here is an overview of services for professionals. In addition, the website is used to promote events related to computational audiology and as a central hub to share resources and funding opportunities, and job opportunities for researchers and clinicians. For clinicians, we added this overview of automated audiometry approaches.

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.

Our VCCA2024 pitch videos offer you a “taster” of what’s to come!  

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

Let’s democratize audiology for persons suffering from hearing loss worldwide. Promote FAIR data policies and Open Science initiatives in audiology for researchers and clinicians. Create methods to deal with the layers of complexity and enhance interoperability. If we work together with all stakeholders involved collaborate on global standards, on a computational infrastructure, and on policies to increase the transparency and responsible use of AI in audiology we can reduce the global burden of hearing loss.

Become member of the Computational Audiology Network. Join the Computational audiology LinkedIn group via this link. Or join our Slack group.

Add your repository to the  Zenodo community for computational audiology via this link.

Read our publication on computational audiology or check out videos below on Computational Audiology TV.

News

Celebrating World Hearing Day

Welcoming New Milestones

Quarterly Update Q13

The latest updates!

Wikipedia

Wikipedia entry about Computational Audiology

Episode 1 Bayesian Active Learning in Audiology

VCCA2024

Last week to register! June 20-21

Computational Audiology Network Slack Channel

Interested in machine learning & big data for audiology, hearing tech, or auditory neuroscience? We started a Slack channel for folks involved in: - basic science & translational research - clinical practice - industry - start ups - public health - health policy and advocacy

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 VCCA2021 conference and repositories published in the Zenodo community for computational audiology. Check out the program highlights for the upcoming VCCA2021 (25 June 2021). All abstracts for VCCA2021 are published on the forum. An overview of the VCCA2020 conference program is provided here. Further backgrounds can be found in the virtual goodiebag.  

More resources and demonstrations

Blogs and conference proceedings

An online workshop designed to equip participants with the essential skills for sharing code and collaborating efficiently using GitHub. Open Read more
We have designed and are trialling Virtual Reality games to help children with bilateral cochlear implants hear better. Read more
We use Bayesian modeling to connect audiology tests such as speech in noise (SPIN) and not only predict missing data, Read more
Vocal emotion recognition in children with hearing aids and children with cochlear implants improves across childhood and adolescence, albeit at Read more
Comparison of the results and perception of a NAO robot and a computer when used for conducting a vocal emotion Read more
This study aims to assess three prominent chatbots - OpenAI ChatGPT, Microsoft Copilot, and Google Gemini - in their ability Read more

The ideas for this website have been published here
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Bibliography:

Wasmann, J.-W. A., & Barbour, D. L. (2021). Emerging Hearing Assessment Technologies for Patient Care. The Hearing Journal, 74(3), 44. https://doi.org/10.1097/01.HJ.0000737596.12888.22
Barbour, D. L., & Wasmann, J.-W. A. (2021). Performance and Potential of Machine Learning Audiometry. The Hearing Journal, 74(3), 40. https://doi.org/10.1097/01.HJ.0000737592.24476.88
Wasmann, J.-W. A., Lanting, C. P., Huinck, W. J., Mylanus, E. A. M., van der Laak, J. W. M., Govaerts, P. J., Swanepoel, D. W., Moore, D. R., & Barbour, D. L. (2021). Computational Audiology: New Approaches to Advance Hearing Health Care in the Digital Age. Ear and Hearing, Publish Ahead of Print. https://doi.org/10.1097/AUD.0000000000001041