# Anonymizing Speech with Generative Adversarial Networks to Preserve Speaker Privacy

arXiv: https://arxiv.org/abs/2210.07002 · HTML: https://mlsanity.com/paper/2210.07002/

## Key facts

- Cited by 21 papers in the map (data through 14 Oct 2026).
- Builds on 27 of its 44 references that are in the map.
- First posted on arXiv 13 Oct 2022.

## Builds on (most cited first, 27 of 27)

- [Deep Residual Learning for Image Recognition](https://mlsanity.com/paper/1512.03385/) (2015)
- [Generative Adversarial Networks](https://mlsanity.com/paper/2203.00667/) (2022)
- [Improved Training of Wasserstein GANs](https://mlsanity.com/paper/1704.00028/) (2017)
- [Conformer: Convolution-augmented Transformer for Speech Recognition](https://mlsanity.com/paper/2005.08100/) (2020)
- [HiFi-GAN: Generative Adversarial Networks for Efficient and High Fidelity Speech Synthesis](https://mlsanity.com/paper/2010.05646/) (2020)
- [VoxCeleb2: Deep Speaker Recognition](https://mlsanity.com/paper/1806.05622/) (2018)
- [Self-Attention Generative Adversarial Networks](https://mlsanity.com/paper/1805.08318/) (2018)
- [VoxCeleb: a large-scale speaker identification dataset](https://mlsanity.com/paper/1706.08612/) (2017)
- [FastSpeech 2: Fast and High-Quality End-to-End Text to Speech](https://mlsanity.com/paper/2006.04558/) (2020)
- [LibriTTS: A Corpus Derived from LibriSpeech for Text-to-Speech](https://mlsanity.com/paper/1904.02882/) (2019)
- [ECAPA-TDNN: Emphasized Channel Attention, Propagation and Aggregation in TDNN Based Speaker Verification](https://mlsanity.com/paper/2005.07143/) (2020)
- [SpeechBrain: A General-Purpose Speech Toolkit](https://mlsanity.com/paper/2106.04624/) (2021)
- [Introducing the VoicePrivacy Initiative](https://mlsanity.com/paper/2005.01387/) (2020)
- [Speaker anonymisation using the McAdams coefficient](https://mlsanity.com/paper/2011.01130/) (2020)
- [Design Choices for X-vector Based Speaker Anonymization](https://mlsanity.com/paper/2005.08601/) (2020)
- [Generative Adversarial Networks: A Survey Towards Private and Secure Applications](https://mlsanity.com/paper/2106.03785/) (2021)
- [The 2020 ESPnet update: new features, broadened applications, performance improvements, and future plans](https://mlsanity.com/paper/2012.13006/) (2020)
- [Language-Independent Speaker Anonymization Approach using Self-Supervised Pre-Trained Models](https://mlsanity.com/paper/2202.13097/) (2022)
- [Adversarial Disentanglement of Speaker Representation for Attribute-Driven Privacy Preservation](https://mlsanity.com/paper/2012.04454/) (2020)
- [Improving speaker de-identification with functional data analysis of f0 trajectories](https://mlsanity.com/paper/2203.16738/) (2022)
- [Speaker Anonymization with Phonetic Intermediate Representations](https://mlsanity.com/paper/2207.04834/) (2022)
- [A Study of F0 Modification for X-Vector Based Speech Pseudonymization Across Gender](https://mlsanity.com/paper/2101.08478/) (2021)
- [Speech Pseudonymisation Assessment Using Voice Similarity Matrices](https://mlsanity.com/paper/2008.13144/) (2020)
- [VoiceMask: Anonymize and Sanitize Voice Input on Mobile Devices](https://mlsanity.com/paper/1711.11460/) (2017)
- [The VoicePrivacy 2020 Challenge Evaluation Plan](https://mlsanity.com/paper/2205.07123/) (2022)
- [Speaker Anonymization with Distribution-Preserving X-Vector Generation for the VoicePrivacy Challenge 2020](https://mlsanity.com/paper/2010.13457/) (2020)
- [Speaker De-identification System using Autoencoders and Adversarial Training](https://mlsanity.com/paper/2011.04696/) (2020)

## Built on by (most cited first, 21 of 21)

- [The VoicePrivacy 2024 Challenge Evaluation Plan](https://mlsanity.com/paper/2404.02677/) (2024)
- [The Impact of Speech Anonymization on Pathology and Its Limits](https://mlsanity.com/paper/2404.08064/) (2024)
- [End-to-end streaming model for low-latency speech anonymization](https://mlsanity.com/paper/2406.09277/) (2024)
- [The Third VoicePrivacy Challenge: Preserving Emotional Expressiveness and Linguistic Content in Voice Anonymization](https://mlsanity.com/paper/2601.11846/) (2026)
- [DarkStream: real-time speech anonymization with low latency](https://mlsanity.com/paper/2509.04667/) (2025)
- [Stream-Voice-Anon: Enhancing Utility of Real-Time Speaker Anonymization via Neural Audio Codec and Language Models](https://mlsanity.com/paper/2601.13948/) (2026)
- [Probing the Feasibility of Multilingual Speaker Anonymization](https://mlsanity.com/paper/2407.02937/) (2024)
- [A Survey of Code-switched Arabic NLP: Progress, Challenges, and Future Directions](https://mlsanity.com/paper/2501.13419/) (2025)
- [TVTSyn: Content-Synchronous Time-Varying Timbre for Streaming Voice Conversion and Anonymization](https://mlsanity.com/paper/2602.09389/) (2026)
- [Vocoder drift compensation by x-vector alignment in speaker anonymisation](https://mlsanity.com/paper/2307.08403/) (2023)
- [Controllable Generation of Artificial Speaker Embeddings through Discovery of Principal Directions](https://mlsanity.com/paper/2310.17502/) (2023)
- [SEF-MK: Speaker-Embedding-Free Voice Anonymization through Multi-k-means Quantization](https://mlsanity.com/paper/2508.07086/) (2025)
- [SegReConcat: A Data Augmentation Method for Voice Anonymization Attack](https://mlsanity.com/paper/2508.18907/) (2025)
- [StreamVoiceAnon+: Emotion-Preserving Streaming Speaker Anonymization via Frame-Level Acoustic Distillation](https://mlsanity.com/paper/2603.06079/) (2026)
- [Privacy-Preserving End-to-End Full-Duplex Speech Dialogue Models](https://mlsanity.com/paper/2603.08179/) (2026)
- [PHONOS: PHOnetic Neutralization for Online Streaming Applications](https://mlsanity.com/paper/2603.27001/) (2026)
- [Anonymization, Not Elimination: Utility-Preserved Speech Anonymization](https://mlsanity.com/paper/2604.17000/) (2026)
- [Scenario of Use Scheme: Threat Model Specification for Speaker Privacy Protection in the Medical Domain](https://mlsanity.com/paper/2409.16106/) (2024)
- [Perceptual implications of automatic anonymization in pathological speech](https://mlsanity.com/paper/2505.00409/) (2025)
- [Your Voice Cloning System is Secretly a Voice Anonymizer](https://mlsanity.com/paper/2608.27360/) (2026)
- [LiveAnon: Improving Privacy and Utility in Streaming Speaker Anonymization with Codec Language Models](https://mlsanity.com/paper/2610.15379/) (2026)

## Abstract (arXiv)

In order to protect the privacy of speech data, speaker anonymization aims for hiding the identity of a speaker by changing the voice in speech recordings. This typically comes with a privacy-utility trade-off between protection of individuals and usability of the data for downstream applications. One of the challenges in this context is to create non-existent voices that sound as natural as possible. In this work, we propose to tackle this issue by generating speaker embeddings using a generative adversarial network with Wasserstein distance as cost function. By incorporating these artificial embeddings into a speech-to-text-to-speech pipeline, we outperform previous approaches in terms of privacy and utility. According to standard objective metrics and human evaluation, our approach generates intelligible and content-preserving yet privacy-protecting versions of the original recordings.