Improving Fairness in Speaker Verification via Group-Adapted Fusion Network
Author:
Affiliation:
1. The Pennsylvania State University
2. Amazon Alexa AI
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9745891/9746004/09747384.pdf?arnumber=9747384
Reference26 articles.
1. Racial disparities in automated speech recognition;koenecke;Proc National Academy of Sciences,2020
2. Fair Voice Biometrics: Impact of Demographic Imbalance on Group Fairness in Speaker Recognition
3. A Survey on Bias and Fairness in Machine Learning
4. Racial Faces in the Wild: Reducing Racial Bias by Information Maximization Adaptation Network
5. Fairness in Recommendation Ranking through Pairwise Comparisons
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2. Golden Gemini is All You Need: Finding the Sweet Spots for Speaker Verification;IEEE/ACM Transactions on Audio, Speech, and Language Processing;2024
3. Fairness and Privacy in Voice Biometrics: A Study of Gender Influences Using wav2vec 2.0;2023 International Conference of the Biometrics Special Interest Group (BIOSIG);2023-09-20
4. TMS: Temporal multi-scale in time-delay neural network for speaker verification;Applied Intelligence;2023-08-25
5. Augmented Datasheets for Speech Datasets and Ethical Decision-Making;2023 ACM Conference on Fairness, Accountability, and Transparency;2023-06-12
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