ICASSP 2023 – A Speech Representation Anonymization Framework via Selective Noise Perturbation

In this episode we discuss A Speech Representation Anonymization Framework via Selective Noise Perturbation
by Minh Tran, Mohammad Soleymani. The paper presents a framework for anonymizing speech data by adding selective noise perturbation to speech representations. It includes a Privacy-risk Saliency Estimator (PSE) that predicts the importance of different representation positions. The approach achieves competitive utility and privacy without re-training any component.