A domain adversarial training (DAT) was developed in a study as a method to reduce gender bias in AI models for depression and PTSD detection using speech data (E-DAIC dataset).
DAT improved F1-scores up to +13% and reduced gender gaps in detection accuracy, improving generalization across male and female participants, specially addressing the effects of the latter’s underrepresentation.
Learn more about this study here: https://doi.org/10.48550/arXiv.2505.03359
Reference
Kim, J., Yoon, H., Oh, W., Jung, D., Yoon, S., Kim, D., Lee, D., Lee, S., & Yang, C. (2025). Domain Adversarial Training for Mitigating Gender Bias in Speech-based Mental Health Detection. 2025 47th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 1-7.