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20242026
most citedAdversarial speech for voice privacy protection from Personalized Speech generation

13 citations · 14 across the 12 of their papers we have counts for

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14 papers

eess.AS2026

Reducing Speaker Residual by Considering Pinhole Effect in Voice Anonymization

Zeyan Liu, Weili Jiang, Liping Chen +4

Voice anonymization aims to protect privacy by suppressing speaker identity while preserving linguistic content and prosody. However, residual speaker attributes in non-identity re…

eess.AS2026

DuraMark: Duration-Embedded Watermarking in LLM-based TTS

Zhenwei Mou, Weili Jiang, Liping Chen +4

Large language model (LLM)-based text-to-speech (TTS) models have achieved remarkable voice cloning capabilities, raising concerns about potential deepfake misuse. Speech watermark…

eess.AS2026

ProSDD: Learning Prosodic Representations for Speech Deepfake Detection against Expressive and Emotional Attacks

Aurosweta Mahapatra, Ismail Rasim Ulgen, Kong Aik Lee +2

Speech deepfake detection (SDD) systems perform well on standard benchmarks datasets but often fail to generalize to expressive and emotional spoofing attacks. Many methods rely on…

eess.AS2025

IDMap: A Pseudo-Speaker Generator Framework Based on Speaker Identity Index to Vector Mapping

Zeyan Liu, Liping Chen, Kong Aik Lee +1

Facilitated by the speech generation framework that disentangles speech into content, speaker, and prosody, voice anonymization is accomplished by substituting the original speaker…

eess.AS2025

A Study of the Removability of Speaker-Adversarial Perturbations

Liping Chen, Chenyang Guo, Kong Aik Lee +2

Recent advancements in adversarial attacks have demonstrated their effectiveness in misleading speaker recognition models, making wrong predictions about speaker identities. On the…

eess.AS2025

Investigation of perception inconsistency in speaker embedding for asynchronous voice anonymization

Rui Wang, Liping Chen, Kong Aik Lee +2

Given the speech generation framework that represents the speaker attribute with an embedding vector, asynchronous voice anonymization can be achieved by modifying the speaker embe…

eess.AS2025★ 1 cited

Speaker Privacy and Security in the Big Data Era: Protection and Defense against Deepfake

Liping Chen, Kong Aik Lee, Zhen-Hua Ling +4

In the era of big data, remarkable advancements have been achieved in personalized speech generation techniques that utilize speaker attributes, including voice and speaking style,…

cs.SD2025

The First Voice Timbre Attribute Detection Challenge

Liping Chen, Jinghao He, Zhengyan Sheng +2

The first voice timbre attribute detection challenge is featured in a special session at NCMMSC 2025. It focuses on the explainability of voice timbre and compares the intensity of…

eess.AS2025

Pinhole Effect on Linkability and Dispersion in Speaker Anonymization

Kong Aik Lee, Zeyan Liu, Liping Chen +1

Speaker anonymization aims to conceal speaker-specific attributes in speech signals, making the anonymized speech unlinkable to the original speaker identity. Recent approaches ach…

cs.SD2025

Introducing voice timbre attribute detection

Jinghao He, Zhengyan Sheng, Liping Chen +2

This paper focuses on explaining the timbre conveyed by speech signals and introduces a task termed voice timbre attribute detection (vTAD). In this task, voice timbre is explained…

cs.SD2025

The Voice Timbre Attribute Detection 2025 Challenge Evaluation Plan

Zhengyan Sheng, Jinghao He, Liping Chen +2

Voice timbre refers to the unique quality or character of a person's voice that distinguishes it from others as perceived by human hearing. The Voice Timbre Attribute Detection (Vt…

cs.SD2024

On the Generation and Removal of Speaker Adversarial Perturbation for Voice-Privacy Protection

Chenyang Guo, Liping Chen, Zhuhai Li +3

Neural networks are commonly known to be vulnerable to adversarial attacks mounted through subtle perturbation on the input data. Recent development in voice-privacy protection has…

cs.SD2024

Asynchronous Voice Anonymization Using Adversarial Perturbation On Speaker Embedding

Rui Wang, Liping Chen, Kong AiK Lee +1

Voice anonymization has been developed as a technique for preserving privacy by replacing the speaker's voice in a speech signal with that of a pseudo-speaker, thereby obscuring th…

eess.AS2024★ 13 cited

Adversarial speech for voice privacy protection from Personalized Speech generation

Shihao Chen, Liping Chen, Jie Zhang +3

The rapid progress in personalized speech generation technology, including personalized text-to-speech (TTS) and voice conversion (VC), poses a challenge in distinguishing between…