Fair EVA is an open source project that is gathering resources and building tools
to help researchers and developers, technology activists and voice technology users
evaluate and audit bias and discrimination in voice technologies.
We are proud to be part of Mozilla's first cohort of projects supported with a Mozilla Technology Fund Award.
to present Benchmark Dataset Dynamics, Bias and Privacy Challenges in Voice Biometrics Research
Our research on bias and privacy challenges in voice biometrics has been featured on the Montreal AI Ethics Blog.
How to we prevent AI from creating deepfakes? Wiebke weighs in on this question on Channel 4 News. Take a look.
Michaela and Anna are premiering a XR Prediction experience inspired by FairEVA in NYC. The Tale False Negative or The Computer Says Nah. Check it out!
After a year of hard work, the bias tests for voice tech python library is ready with bias evaluations for speaker verification. Check it out: https://github.com/wiebket/bt4vt
We have published the results of our dataset audit. Read it here: About Voice: A Longitudinal Study of Speaker Recognition Dataset Dynamics
We have published a technical analysis of design considerations for robust and inclusive speaker verification evaluation. Read it here: Design Guidelines for Inclusive Speaker Verification Evaluation Datasets
Fair EVA project lead, Wiebke Hutiri, shares her perspectives on voice biometrics and the proposed EU AI Act in the Mozilla Blog. Read it here: The Proposed EU AI Act and The Case of Biometrics
The EAB invited us to present our work on voice recognition at the Artificial Intelligence Act Workshop 2022.
The research that forms the foundation of FairEVA will be presented at the ACM FAccT 2022 conference. Take a read:
Bias in Automated Speaker Recognition
Read more about Fair EVA and why we exist in this blog post: Access Denied! This Doesn’t Sound Like You
We hosted a session on Fair Voice: What happens when your voice becomes your ID? at MozFest 2022, with panelists Halsey Burgund, Johann Diedrick, Kathleen Siminyu and Wiebke Hutiri.