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arXiv · 2409.04173

NPU-NTU System for Voice Privacy 2024 Challenge

Jixun Yao·Nikita Kuzmin·Qing Wang·Pengcheng Guo·Ziqian Ning·Dake Guo·Kong Aik Lee·Eng-Siong Chng·Lei Xie
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Abstract

Speaker anonymization is an effective privacy protection solution that conceals the speaker's identity while preserving the linguistic content and paralinguistic information of the original speech. To establish a fair benchmark and facilitate comparison of speaker anonymization systems, the VoicePrivacy Challenge (VPC) was held in 2020 and 2022, with a new edition planned for 2024. In this paper, we describe our proposed speaker anonymization system for VPC 2024. Our system employs a disentangled neural codec architecture and a serial disentanglement strategy to gradually disentangle the global speaker identity and time-variant linguistic content and paralinguistic information. We introduce multiple distillation methods to disentangle linguistic content, speaker identity, and emotion. These methods include semantic distillation, supervised speaker distillation, and frame-level emotion distillation. Based on these distillations, we anonymize the original speaker identity using a weighted sum of a set of candidate speaker identities and a randomly generated speaker identity. Our system achieves the best trade-off of privacy protection and emotion preservation in VPC 2024.

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Jixun Yao, Nikita Kuzmin, Qing Wang, Pengcheng Guo, Ziqian Ning, Dake Guo, Kong Aik Lee, Eng-Siong Chng, Lei Xie. 2025-02-04. NPU-NTU System for Voice Privacy 2024 Challenge. https://arxiv.org/abs/2409.04173

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