3 papers
eess.AS2024
Investigating Effective Speaker Property Privacy Protection in Federated Learning for Speech Emotion Recognition
Chao Tan, Sheng Li, Yang Cao +2
Federated Learning (FL) is a privacy-preserving approach that allows servers to aggregate distributed models transmitted from local clients rather than training on user data. More…
eess.AS2023
GhostVec: A New Threat to Speaker Privacy of End-to-End Speech Recognition System
Xiaojiao Chen, Sheng Li, Jiyi Li +3
Speaker adaptation systems face privacy concerns, for such systems are trained on private datasets and often overfitting. This paper demonstrates that an attacker can extract speak…
eess.AS2023
Reprogramming Self-supervised Learning-based Speech Representations for Speaker Anonymization
Xiaojiao Chen, Sheng Li, Jiyi Li +3
Current speaker anonymization methods, especially with self-supervised learning (SSL) models, require massive computational resources when hiding speaker identity. This paper propo…