34 citations · 66 across the 22 of their papers we have counts for
22 papers
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…
Bayesian Learning for Domain-Invariant Speaker Verification and Anti-Spoofing
Jin Li, Man-Wai Mak, Johan Rohdin +2
The performance of automatic speaker verification (ASV) and anti-spoofing drops seriously under real-world domain mismatch conditions. The relaxed instance frequency-wise normaliza…
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…
Malacopula: adversarial automatic speaker verification attacks using a neural-based generalised Hammerstein model
Massimiliano Todisco, Michele Panariello, Xin Wang +3
We present Malacopula, a neural-based generalised Hammerstein model designed to introduce adversarial perturbations to spoofed speech utterances so that they better deceive automat…
ASVspoof 5: Crowdsourced Speech Data, Deepfakes, and Adversarial Attacks at Scale
Xin Wang, Hector Delgado, Hemlata Tak +10
ASVspoof 5 is the fifth edition in a series of challenges that promote the study of speech spoofing and deepfake attacks, and the design of detection solutions. Compared to previou…