Why Computational Audiology ?

The purpose of this online forum is to share knowledge and tools related to 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 and as a central hub to share resources and funding opportunities that are useful for researchers and clinicians.

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

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.

Join the Computational audiology LinkedIn group via this link.

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

Read our publication on computational audiology or check out videos on our youtube Channel

News & Agenda

Quarterly Update Q1

Call for abstracts VCCA2021 is open! Winner Computational audiology prize announced, and check out recent publications.

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.

VCCA2021 Call for Abstracts

The Virtual Conference on Computational Audiology 2021 (VCCA 2021) will be soon accepting abstracts on research, innovative projects, software, tools and other applications related to Computational Audiology.

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 and repositories published in the Zenodo community for computational audiology. An overview of the VCCA2020 conference program is provided here. Further backgrounds can be the virtual goodiebag.  

Zenodo Repositories:

8 documents
  • tobiasherzke, Paul Maanen, frasherloshaj, hendrikkayser, Marc Joliet, genckamil, steffendasenbrock, Giso Grimm, Muhammad Zain Sohail. (March, 2021). HoerTech-gGmbH/openMHA: Release 4.15.0 (Version v4.15.0). Zenodo. https://doi.org/10.5281/zenodo.4650058
  • Zinner, Christina, Winkler, Alexandra, Holube, Inga. (March, 2021). Speech Adjusted Noises (SAN) for German speech recognition tests. Zenodo. https://doi.org/10.5281/zenodo.4609783
  • Hendrik Kayser, Tobias Herzke, Paul Maanen, Max Zimmermann, Giso Grimm, Volker Hohmann. (March, 2021). Open community platform for hearing aid algorithm research: open Master Hearing Aid (openMHA). Zenodo. https://doi.org/10.5281/zenodo.4601604
  • Nuesse, Theresa, Wiercinski, Bianca, Holube, Inga. (February, 2021). Synthetic German matrix speech test material created with a text-to-speech system (Version Version 1 (zipped)). Zenodo. https://doi.org/10.5281/zenodo.4522088
  • Raul Sanchez-Lopez, Fereczkowski, Michal, Santurette, Sébastien, Dau, Torsten, Neher, Tobias. (April, 2020). Data and materials from: “Towards Auditory Profile-based Hearing-aid Fitting: Fitting Rationale and Pilot Evaluation” (Version 1.1). Zenodo. https://doi.org/10.5281/zenodo.4421553
  • Sanchez-Lopez, Raul, Nielsen, Silje Grini, El-Haj-Ali, Mouhamad, Bianchi, Federica, Fereczkowski, Michal, Cañete, Oscar, Wu, Mengfan, Neher, Tobias, Dau, Torsten, Sébastien Santurette. (December, 2019). Data from “Auditory tests for characterizing hearing deficits: The BEAR test battery” (Version v1.0). Zenodo. https://doi.org/10.5281/zenodo.3459580
  • Hohmann, Volker, Herzke, Tobias. (February, 2007). Software for “Frequency analysis and synthesis using a Gammatone filterbank” (Version 1.1). Zenodo. https://doi.org/10.5281/zenodo.2643400
  • Josupeit, Angela, Schoenmaker, Esther, van de Par, Steven, Hohmann, Volker. (May, 2018). Raw data for “Sparse periodicity-based auditory features explain human performance in a spatial multi-talker auditory scene analysis task”. Zenodo. https://doi.org/10.5281/zenodo.1246836

More resources and demonstrations

Blogs and conference proceedings

The COVID-19 crisis has rapidly and dramatically expanded the global interest in and demand for tele-audiology services, even in highly Read more
Although cochlear implants (CIs) provide hearing for severely-hearing-impaired or deaf populations, certain hearing abilities remain challenging for CI users. Read more
Design and evaluation of a real-time audio source separation algorithm to remix music for cochlear implant users Read more
Auditory modeling is indispensable for precision diagnostics and individualized treatment Read more
Simulated binaural neural networks show that sharp spatial and frequency tuning is needed to accurately localize sound sources in the Read more
AI-assisted Diagnosis for Middle Ear Pathologies Read more
The biggest hurdle facing computational audiologists may not be perfecting machine learning methods, but creating the infrastructure- including hardware, data Read more
Remote Audiology Delivery Care COVID-19 Read more
Modeling speech perception in hidden hearing loss using stochastically undersampled neuronal firing patterns Read more
Speech perception by hearing aid (HA) users has been evaluated in a database that includes up to 45 hours of Read more

The ideas for this website have been published here


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