1 citations · 1 across the 13 of their papers we have counts for
15 papers
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…
Dynamic Prosody Prediction in LLM-based TTS for Improving Speaker Similarity
Zhenwei Mou, Liping Chen, Yajun Hu +3
Personalized text-to-speech (TTS) aims to clone the target speaker in the synthesized speech, imitating both the voice and speaking style. Current large language model (LLM)-based…
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…
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…
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…
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…
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,…
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…
Any-to-any Speaker Attribute Perturbation for Asynchronous Voice Anonymization
Liping Chen, Chenyang Guo, Rui Wang +2
Speaker attribute perturbation offers a feasible approach to asynchronous voice anonymization by employing adversarially perturbed speech as anonymized output. In order to enhance…
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…
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…
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…
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…
Refining Self-Supervised Learnt Speech Representation using Brain Activations
Hengyu Li, Kangdi Mei, Zhaoci Liu +4
It was shown in literature that speech representations extracted by self-supervised pre-trained models exhibit similarities with brain activations of human for speech perception an…
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…