14 papers
GenTraceBench: A Benchmark for Tracing Audio Deepfakes Across Pre- and Post-training Stages
Li Wang, Kunyu Feng, Wan Lin +7
Modern text-to-speech (TTS) systems are rarely deployed as unchanged pre-trained models. They are often adapted through supervised fine-tuning (SFT) or preference optimization such…
CoReLoop: Parameter-Efficient Controlled Recurrent Refinement for Audio Deepfake Detection
Kunyu Feng, Yuxiang Wang, Li Wang +2
Audio deepfake detectors are expected to remain robust to diverse attacks, datasets, and recording conditions, yet collecting training data that cover every future condition is imp…
Teffic-Audio: Tell Fact from Fiction
Wan Lin, Li Wang, Jindong Wang +2
Speech deepfake detection has expanded in scope with increasingly heterogeneous spoofing mechanisms, including speech synthesis, voice conversion, vocoder reconstruction, and neura…
VoxSafeBench: Not Just What Is Said, but Who, How, and Where
Yuxiang Wang, Hongyu Liu, Yijiang Xu +9
As speech language models (SLMs) transition from personal devices into shared, multi-user environments, their responses must account for far more than the words alone. Who is speak…
DFALLM: Achieving Generalizable Multitask Deepfake Detection by Optimizing Audio LLM Components
Yupei Li, Li Wang, Yuxiang Wang +5
Audio deepfake detection has recently garnered public concern due to its implications for security and reliability. Traditional deep learning methods have been widely applied to th…
SpeechJudge: Towards Human-Level Judgment for Speech Naturalness
Xueyao Zhang, Chaoren Wang, Huan Liao +8
Aligning large generative models with human feedback is a critical challenge. In speech synthesis, this is particularly pronounced due to the lack of a large-scale human preference…
Over-the-Air Adversarial Attack Detection: from Datasets to Defenses
Li Wang, Xiaoyan Lei, Haorui He +3
Automatic Speaker Verification (ASV) systems can be used for voice-enabled applications for identity verification. However, recent studies have exposed these systems' vulnerabiliti…
Audio Deepfake Verification
Li Wang, Junyi Ao, Linyong Gan +3
With the rapid development of deepfake technology, simply making a binary judgment of true or false on audio is no longer sufficient to meet practical needs. Accurately determining…
Overview of the Amphion Toolkit (v0.2)
Jiaqi Li, Xueyao Zhang, Yuancheng Wang +9
Amphion is an open-source toolkit for Audio, Music, and Speech Generation, designed to lower the entry barrier for junior researchers and engineers in these fields. It provides a v…
Noro: Noise-Robust One-shot Voice Conversion with Hidden Speaker Representation Learning
Haorui He, Yuchen Song, Yuancheng Wang +6
The effectiveness of one-shot voice conversion (VC) decreases in real-world scenarios where reference speeches, which are often sourced from the internet, contain various disturban…
SpMis: An Investigation of Synthetic Spoken Misinformation Detection
Peizhuo Liu, Li Wang, Renqiang He +6
In recent years, speech generation technology has advanced rapidly, fueled by generative models and large-scale training techniques. While these developments have enabled the produ…
Audio compression-assisted feature extraction for voice replay attack detection
Xiangyu Shi, Yuhao Luo, Li Wang +4
Replay attack is one of the most effective and simplest voice spoofing attacks. Detecting replay attacks is challenging, according to the Automatic Speaker Verification Spoofing an…
AdvSV: An Over-the-Air Adversarial Attack Dataset for Speaker Verification
Li Wang, Jiaqi Li, Yuhao Luo +7
It is known that deep neural networks are vulnerable to adversarial attacks. Although Automatic Speaker Verification (ASV) built on top of deep neural networks exhibits robust perf…
An Initial Investigation of Neural Replay Simulator for Over-the-Air Adversarial Perturbations to Automatic Speaker Verification
Jiaqi Li, Li Wang, Liumeng Xue +2
Deep Learning has advanced Automatic Speaker Verification (ASV) in the past few years. Although it is known that deep learning-based ASV systems are vulnerable to adversarial examp…