# NPU-NTU System for Voice Privacy 2024 Challenge

arXiv: https://arxiv.org/abs/2409.04173 · HTML: https://mlsanity.com/paper/2409.04173/

## Key facts

- Cited by 14 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 6 Sep 2024.

## Built on by (most cited first, 14 of 14)

- [The Third VoicePrivacy Challenge: Preserving Emotional Expressiveness and Linguistic Content in Voice Anonymization](https://mlsanity.com/paper/2601.11846/) (2026)
- [Stream-Voice-Anon: Enhancing Utility of Real-Time Speaker Anonymization via Neural Audio Codec and Language Models](https://mlsanity.com/paper/2601.13948/) (2026)
- [TVTSyn: Content-Synchronous Time-Varying Timbre for Streaming Voice Conversion and Anonymization](https://mlsanity.com/paper/2602.09389/) (2026)
- [The First VoicePrivacy Attacker Challenge](https://mlsanity.com/paper/2504.14183/) (2025)
- [Exploiting Context-dependent Duration Features for Voice Anonymization Attack Systems](https://mlsanity.com/paper/2507.15214/) (2025)
- [The First VoicePrivacy Attacker Challenge Evaluation Plan](https://mlsanity.com/paper/2410.07428/) (2024)
- [Universal Semantic Disentangled Privacy-preserving Speech Representation Learning](https://mlsanity.com/paper/2505.13085/) (2025)
- [SegReConcat: A Data Augmentation Method for Voice Anonymization Attack](https://mlsanity.com/paper/2508.18907/) (2025)
- [Target speaker anonymization in multi-speaker recordings](https://mlsanity.com/paper/2510.09307/) (2025)
- [StreamVoiceAnon+: Emotion-Preserving Streaming Speaker Anonymization via Frame-Level Acoustic Distillation](https://mlsanity.com/paper/2603.06079/) (2026)
- [Variational Encoder--Multi-Decoder (VE-MD) for Privacy-by-functional-design (Group) Emotion Recognition](https://mlsanity.com/paper/2604.02397/) (2026)
- [DiffAnon: Diffusion-based Prosody Control for Voice Anonymization](https://mlsanity.com/paper/2604.26281/) (2026)
- [Multimodal Group Emotion Recognition In-the-Wild Towards a Privacy-Safe Non-Individual Approach](https://mlsanity.com/paper/2606.07585/) (2026)
- [LiveAnon: Improving Privacy and Utility in Streaming Speaker Anonymization with Codec Language Models](https://mlsanity.com/paper/2610.15379/) (2026)

## Abstract (arXiv)

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.