83 citations · 166 across the 57 of their papers we have counts for
8 papers · 1 filter
Dual-Branch Knowledge Distillation for Noise-Robust Synthetic Speech Detection
Cunhang Fan, Mingming Ding, Jianhua Tao +4
Most research in synthetic speech detection (SSD) focuses on improving performance on standard noise-free datasets. However, in actual situations, noise interference is usually pre…
Learning Speech Representation From Contrastive Token-Acoustic Pretraining
Chunyu Qiang, Hao Li, Yixin Tian +4
For fine-grained generation and recognition tasks such as minimally-supervised text-to-speech (TTS), voice conversion (VC), and automatic speech recognition (ASR), the intermediate…
Minimally-Supervised Speech Synthesis with Conditional Diffusion Model and Language Model: A Comparative Study of Semantic Coding
Chunyu Qiang, Hao Li, Hao Ni +5
Recently, there has been a growing interest in text-to-speech (TTS) methods that can be trained with minimal supervision by combining two types of discrete speech representations a…
Low-rank Adaptation Method for Wav2vec2-based Fake Audio Detection
Chenglong Wang, Jiangyan Yi, Xiaohui Zhang +3
Self-supervised speech models are a rapidly developing research topic in fake audio detection. Many pre-trained models can serve as feature extractors, learning richer and higher-l…
Adaptive Fake Audio Detection with Low-Rank Model Squeezing
Xiaohui Zhang, Jiangyan Yi, Jianhua Tao +3
The rapid advancement of spoofing algorithms necessitates the development of robust detection methods capable of accurately identifying emerging fake audio. Traditional approaches,…
ADD 2023: the Second Audio Deepfake Detection Challenge
Jiangyan Yi, Jianhua Tao, Ruibo Fu +15
Audio deepfake detection is an emerging topic in the artificial intelligence community. The second Audio Deepfake Detection Challenge (ADD 2023) aims to spur researchers around the…
TO-Rawnet: Improving RawNet with TCN and Orthogonal Regularization for Fake Audio Detection
Chenglong Wang, Jiangyan Yi, Jianhua Tao +4
Current fake audio detection relies on hand-crafted features, which lose information during extraction. To overcome this, recent studies use direct feature extraction from raw audi…
UnifySpeech: A Unified Framework for Zero-shot Text-to-Speech and Voice Conversion
Haogeng Liu, Tao Wang, Ruibo Fu +3
Text-to-speech (TTS) and voice conversion (VC) are two different tasks both aiming at generating high quality speaking voice according to different input modality. Due to their sim…