16 citations · 82 across the 23 of their papers we have counts for
23 papers
Scalable Ensemble-based Detection Method against Adversarial Attacks for speaker verification
Haibin Wu, Heng-Cheng Kuo, Yu Tsao +1
Automatic speaker verification (ASV) is highly susceptible to adversarial attacks. Purification modules are usually adopted as a pre-processing to mitigate adversarial noise. Howev…
The defender's perspective on automatic speaker verification: An overview
Haibin Wu, Jiawen Kang, Lingwei Meng +2
Automatic speaker verification (ASV) plays a critical role in security-sensitive environments. Regrettably, the reliability of ASV has been undermined by the emergence of spoofing…
SpeechGen: Unlocking the Generative Power of Speech Language Models with Prompts
Haibin Wu, Kai-Wei Chang, Yuan-Kuei Wu +1
Large language models (LLMs) have gained considerable attention for Artificial Intelligence Generated Content (AIGC), particularly with the emergence of ChatGPT. However, the direc…
Unified Modeling of Multi-Talker Overlapped Speech Recognition and Diarization with a Sidecar Separator
Lingwei Meng, Jiawen Kang, Mingyu Cui +3
Multi-talker overlapped speech poses a significant challenge for speech recognition and diarization. Recent research indicated that these two tasks are inter-dependent and compleme…
Rethinking complex-valued deep neural networks for monaural speech enhancement
Haibin Wu, Ke Tan, Buye Xu +2
Despite multiple efforts made towards adopting complex-valued deep neural networks (DNNs), it remains an open question whether complex-valued DNNs are generally more effective than…
SUPERB @ SLT 2022: Challenge on Generalization and Efficiency of Self-Supervised Speech Representation Learning
Tzu-hsun Feng, Annie Dong, Ching-Feng Yeh +11
We present the SUPERB challenge at SLT 2022, which aims at learning self-supervised speech representation for better performance, generalization, and efficiency. The challenge buil…
Push-Pull: Characterizing the Adversarial Robustness for Audio-Visual Active Speaker Detection
Xuanjun Chen, Haibin Wu, Helen Meng +2
Audio-visual active speaker detection (AVASD) is well-developed, and now is an indispensable front-end for several multi-modal applications. However, to the best of our knowledge,…
Multimodal Transformer Distillation for Audio-Visual Synchronization
Xuanjun Chen, Haibin Wu, Chung-Che Wang +2
Audio-visual synchronization aims to determine whether the mouth movements and speech in the video are synchronized. VocaLiST reaches state-of-the-art performance by incorporating…
Tackling Spoofing-Aware Speaker Verification with Multi-Model Fusion
Haibin Wu, Jiawen Kang, Lingwei Meng +5
Recent years have witnessed the extraordinary development of automatic speaker verification (ASV). However, previous works show that state-of-the-art ASV models are seriously vulne…
Spoofing-Aware Speaker Verification by Multi-Level Fusion
Haibin Wu, Lingwei Meng, Jiawen Kang +5
Recently, many novel techniques have been introduced to deal with spoofing attacks, and achieve promising countermeasure (CM) performances. However, these works only take the stand…
MFA-Conformer: Multi-scale Feature Aggregation Conformer for Automatic Speaker Verification
Yang Zhang, Zhiqiang Lv, Haibin Wu +5
In this paper, we present Multi-scale Feature Aggregation Conformer (MFA-Conformer), an easy-to-implement, simple but effective backbone for automatic speaker verification based on…
Partially Fake Audio Detection by Self-attention-based Fake Span Discovery
Haibin Wu, Heng-Cheng Kuo, Naijun Zheng +5
The past few years have witnessed the significant advances of speech synthesis and voice conversion technologies. However, such technologies can undermine the robustness of broadly…
The CUHK-TENCENT speaker diarization system for the ICASSP 2022 multi-channel multi-party meeting transcription challenge
Naijun Zheng, Na Li, Xixin Wu +6
This paper describes our speaker diarization system submitted to the Multi-channel Multi-party Meeting Transcription (M2MeT) challenge, where Mandarin meeting data were recorded in…
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…
Voting for the right answer: Adversarial defense for speaker verification
Haibin Wu, Yang Zhang, Zhiyong Wu +2
Automatic speaker verification (ASV) is a well developed technology for biometric identification, and has been ubiquitous implemented in security-critic applications, such as banki…
Adversarial Sample Detection for Speaker Verification by Neural Vocoders
Haibin Wu, Po-chun Hsu, Ji Gao +6
Automatic speaker verification (ASV), one of the most important technology for biometric identification, has been widely adopted in security-critical applications. However, ASV is…
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…
Tackling Variabilities in Autonomous Driving
Yuqiong Qi, Yang Hu, Haibin Wu +5
The state-of-the-art driving automation system demands extreme computational resources to meet rigorous accuracy and latency requirements. Though emerging driving automation comput…
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…
QR-MIX: Distributional Value Function Factorisation for Cooperative Multi-Agent Reinforcement Learning
Jian Hu, Seth Austin Harding, Haibin Wu +2
In Cooperative Multi-Agent Reinforcement Learning (MARL) and under the setting of Centralized Training with Decentralized Execution (CTDE), agents observe and interact with their e…
Defense for Black-box Attacks on Anti-spoofing Models by Self-Supervised Learning
Haibin Wu, Andy T. Liu, Hung-yi Lee
High-performance anti-spoofing models for automatic speaker verification (ASV), have been widely used to protect ASV by identifying and filtering spoofing audio that is deliberatel…
Defense against adversarial attacks on spoofing countermeasures of ASV
Haibin Wu, Songxiang Liu, Helen Meng +1
Various forefront countermeasure methods for automatic speaker verification (ASV) with considerable performance in anti-spoofing are proposed in the ASVspoof 2019 challenge. Howeve…
Adversarial Attacks on Spoofing Countermeasures of automatic speaker verification
Songxiang Liu, Haibin Wu, Hung-yi Lee +1
High-performance spoofing countermeasure systems for automatic speaker verification (ASV) have been proposed in the ASVspoof 2019 challenge. However, the robustness of such systems…