@inproceedings{177671ba1d184576907ad952293e2122,
title = "Voice Doppelg{\"a}nger Susceptibility among Racial and Gender Groups: IEEE CNS 21 Poster",
abstract = "Voice doppelganger describes a person or thing that sounds like another, which is considered a potential security risk for voice biometrics. Considering that racial or gender groups have different biological vocal structures, it is possible that these subgroups have different vulnerabilities to the voice doppelganger and voice biometrics. This study investigates if racial and gender disparities exist in the security risk of the voice doppelganger towards the voice biometric. We used three different metrics to measure voice similarity: fundamental frequency, MFCCs, and pitch. The result was that persons within gender and racial subgroups do indeed sound more similar to each other, with racial subgroups displaying more similarity than gender.",
keywords = "fairness, voice biometrics, voice doppelganger",
author = "Emily Wu and Zhengxiong Li and Wenyao Xu",
note = "Publisher Copyright: {\textcopyright} 2021 IEEE.; 2021 IEEE Conference on Communications and Network Security, CNS 2021 ; Conference date: 04-10-2021 Through 06-10-2021",
year = "2021",
doi = "10.1109/CNS53000.2021.9729035",
language = "English",
series = "2021 IEEE Conference on Communications and Network Security, CNS 2021",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2021 IEEE Conference on Communications and Network Security, CNS 2021",
address = "United States",
}