18 citations · 71 across the 14 of their papers we have counts for
5 papers · 1 filter
Characterizing the adversarial vulnerability of speech self-supervised learning
Haibin Wu, Bo Zheng, Xu Li +3
A leaderboard named Speech processing Universal PERformance Benchmark (SUPERB), which aims at benchmarking the performance of a shared self-supervised learning (SSL) speech model a…
Channel-wise Gated Res2Net: Towards Robust Detection of Synthetic Speech Attacks
Xu Li, Xixin Wu, Hui Lu +2
Existing approaches for anti-spoofing in automatic speaker verification (ASV) still lack generalizability to unseen attacks. The Res2Net approach designs a residual-like connection…
VAENAR-TTS: Variational Auto-Encoder based Non-AutoRegressive Text-to-Speech Synthesis
Hui Lu, Zhiyong Wu, Xixin Wu +4
This paper describes a variational auto-encoder based non-autoregressive text-to-speech (VAENAR-TTS) model. The autoregressive TTS (AR-TTS) models based on the sequence-to-sequence…
Improving the Adversarial Robustness for Speaker Verification by Self-Supervised Learning
Haibin Wu, Xu Li, Andy T. Liu +3
Previous works have shown that automatic speaker verification (ASV) is seriously vulnerable to malicious spoofing attacks, such as replay, synthetic speech, and recently emerged ad…
Adversarial defense for automatic speaker verification by cascaded self-supervised learning models
Haibin Wu, Xu Li, Andy T. Liu +3
Automatic speaker verification (ASV) is one of the core technologies in biometric identification. With the ubiquitous usage of ASV systems in safety-critical applications, more and…