24 citations · 60 across the 37 of their papers we have counts for
39 papers
Voice Anonymization Made Simple: Training-Free Anonymization with Projected Classifier-Free Guidance
Xiang Shi, Han Zhu, Ming Li +1
Voice anonymization aims to conceal speaker identity while preserving linguistic and paralinguistic information, yet many existing methods require dedicated training. We propose a…
Exploiting Acoustic and Content-Oriented Speaker Verification Attacks Against Multilingual Voice Anonymization
Ridwan Arefeen, Ze Li, Rong Tong +2
Attacker ASV systems for voice anonymization have been studied primarily in English, leaving their behavior in multilingual settings largely unexplored. Conventional ASV has shown…
In Defense of Using Worst-case Privacy Disclosure as Privacy Evaluation Metric of Voice Anonymization
Xin Wang, Xiaoxiao Miao
The voice anonymization community mainly uses Equal Error Rate (EER) to evaluate the performance of voice identity protection. While alternative metrics such as privacy-ZEBRA and a…
Child-Centric Voice Anonymization in Single and Multi-Speaker Speech via Domain-Adapted SSL Models
Pranav Tushar, Xiao Xiao Miao, Rong Tong
Voice anonymization aims to protect speaker identity while preserving linguistic content and speech usability. However, most anonymization systems are developed on adult speech, le…
Spectrogram features for audio and speech analysis
Ian McLoughlin, Lam Pham, Yan Song +7
Spectrogram-based representations have grown to dominate the feature space for deep learning audio analysis systems, and are often adopted for speech analysis also. Initially, the…
DAST: A Dual-Stream Voice Anonymization Attacker with Staged Training
Ridwan Arefeen, Xiaoxiao Miao, Rong Tong +3
Voice anonymization masks vocal traits while preserving linguistic content, which may still leak speaker-specific patterns. To assess and strengthen privacy evaluation, we propose…
Language-Invariant Multilingual Speaker Verification for the TidyVoice 2026 Challenge
Ze Li, Xiaoxiao Miao, Juan Liu +1
Multilingual speaker verification (SV) remains challenging due to limited cross-lingual data and language-dependent information in speaker embeddings. This paper presents a languag…
Toward Multimodal Industrial Fault Analysis: A Single-Speed Chain Conveyor Dataset with Audio and Vibration Signals
Zhang Chen, Yucong Zhang, Xiaoxiao Miao +1
We introduce a multimodal industrial fault analysis dataset collected from a single-speed chain conveyor (SSCC) system, targeting system-level fault detection in production lines.…
Training Dynamics-Aware Multi-Factor Curriculum Learning for Target Speaker Extraction
Yun Liu, Xuechen Liu, Xiaoxiao Miao +1
Target speaker extraction (TSE) aims to isolate a specific speaker's voice from multi-speaker mixtures. Despite strong benchmark results, real-world performance often degrades due…
The Third VoicePrivacy Challenge: Preserving Emotional Expressiveness and Linguistic Content in Voice Anonymization
Natalia Tomashenko, Xiaoxiao Miao, Pierre Champion +7
We present results and analyses from the third VoicePrivacy Challenge held in 2024, which focuses on advancing voice anonymization technologies. The task was to develop a voice ano…
SegReConcat: A Data Augmentation Method for Voice Anonymization Attack
Ridwan Arefeen, Xiaoxiao Miao, Rong Tong +2
Anonymization of voice seeks to conceal the identity of the speaker while maintaining the utility of speech data. However, residual speaker cues often persist, which pose privacy r…
SEF-MK: Speaker-Embedding-Free Voice Anonymization through Multi-k-means Quantization
Beilong Tang, Xiaoxiao Miao, Xin Wang +1
Voice anonymization protects speaker privacy by concealing identity while preserving linguistic and paralinguistic content. Self-supervised learning (SSL) representations encode li…
The Risks and Detection of Overestimated Privacy Protection in Voice Anonymisation
Michele Panariello, Sarina Meyer, Pierre Champion +4
Voice anonymisation aims to conceal the voice identity of speakers in speech recordings. Privacy protection is usually estimated from the difficulty of using a speaker verification…
SecureSpeech: Prompt-based Speaker and Content Protection
Belinda Soh Hui Hui, Xiaoxiao Miao, Xin Wang
Given the increasing privacy concerns from identity theft and the re-identification of speakers through content in the speech field, this paper proposes a prompt-based speech gener…
Mitigating Language Mismatch in SSL-Based Speaker Anonymization
Zhe Zhang, Wen-Chin Huang, Xin Wang +2
Speaker anonymization aims to protect speaker identity while preserving content information and the intelligibility of speech. However, most speaker anonymization systems (SASs) ar…
Automated evaluation of children's speech fluency for low-resource languages
Bowen Zhang, Nur Afiqah Abdul Latiff, Justin Kan +4
Assessment of children's speaking fluency in education is well researched for majority languages, but remains highly challenging for low resource languages. This paper proposes a s…
The First VoicePrivacy Attacker Challenge
Natalia Tomashenko, Xiaoxiao Miao, Emmanuel Vincent +1
The First VoicePrivacy Attacker Challenge is an ICASSP 2025 SP Grand Challenge which focuses on evaluating attacker systems against a set of voice anonymization systems submitted t…
Libri2Vox Dataset: Target Speaker Extraction with Diverse Speaker Conditions and Synthetic Data
Yun Liu, Xuechen Liu, Xiaoxiao Miao +1
Target speaker extraction (TSE) is essential in speech processing applications, particularly in scenarios with complex acoustic environments. Current TSE systems face challenges in…
The First VoicePrivacy Attacker Challenge Evaluation Plan
Natalia Tomashenko, Xiaoxiao Miao, Emmanuel Vincent +1
The First VoicePrivacy Attacker Challenge is a new kind of challenge organized as part of the VoicePrivacy initiative and supported by ICASSP 2025 as the SP Grand Challenge It focu…
InstructSing: High-Fidelity Singing Voice Generation via Instructing Yourself
Chang Zeng, Chunhui Wang, Xiaoxiao Miao +3
It is challenging to accelerate the training process while ensuring both high-quality generated voices and acceptable inference speed. In this paper, we propose a novel neural voco…
Spoofing-Aware Speaker Verification Robust Against Domain and Channel Mismatches
Chang Zeng, Xiaoxiao Miao, Xin Wang +2
In real-world applications, it is challenging to build a speaker verification system that is simultaneously robust against common threats, including spoofing attacks, channel misma…
Adapting General Disentanglement-Based Speaker Anonymization for Enhanced Emotion Preservation
Xiaoxiao Miao, Yuxiang Zhang, Xin Wang +3
A general disentanglement-based speaker anonymization system typically separates speech into content, speaker, and prosody features using individual encoders. This paper explores h…
The VoicePrivacy 2022 Challenge: Progress and Perspectives in Voice Anonymisation
Michele Panariello, Natalia Tomashenko, Xin Wang +7
The VoicePrivacy Challenge promotes the development of voice anonymisation solutions for speech technology. In this paper we present a systematic overview and analysis of the secon…
A Benchmark for Multi-speaker Anonymization
Xiaoxiao Miao, Ruijie Tao, Chang Zeng +1
Privacy-preserving voice protection approaches primarily suppress privacy-related information derived from paralinguistic attributes while preserving the linguistic content. Existi…