24 citations · 32 across the 23 of their papers we have counts for
11 papers · 1 filter
M3-TTS: Multi-modal DiT Alignment & Mel-latent for Zero-shot High-fidelity Speech Synthesis
Xiaopeng Wang, Chunyu Qiang, Ruibo Fu +10
Non-autoregressive (NAR) text-to-speech synthesis relies on length alignment between text sequences and audio representations, constraining naturalness and expressiveness. Existing…
RPRA-ADD: Forgery Trace Enhancement-Driven Audio Deepfake Detection
Ruibo Fu, Xiaopeng Wang, Zhengqi Wen +8
Existing methods for deepfake audio detection have demonstrated some effectiveness. However, they still face challenges in generalizing to new forgery techniques and evolving attac…
Mel-Refine: A Plug-and-Play Approach to Refine Mel-Spectrogram in Audio Generation
Hongming Guo, Ruibo Fu, Yizhong Geng +9
Text-to-audio (TTA) model is capable of generating diverse audio from textual prompts. However, most mainstream TTA models, which predominantly rely on Mel-spectrograms, still face…
Mixture of Experts Fusion for Fake Audio Detection Using Frozen wav2vec 2.0
Zhiyong Wang, Ruibo Fu, Zhengqi Wen +10
Speech synthesis technology has posed a serious threat to speaker verification systems. Currently, the most effective fake audio detection methods utilize pretrained models, and in…
DPI-TTS: Directional Patch Interaction for Fast-Converging and Style Temporal Modeling in Text-to-Speech
Xin Qi, Ruibo Fu, Zhengqi Wen +12
In recent years, speech diffusion models have advanced rapidly. Alongside the widely used U-Net architecture, transformer-based models such as the Diffusion Transformer (DiT) have…
EELE: Exploring Efficient and Extensible LoRA Integration in Emotional Text-to-Speech
Xin Qi, Ruibo Fu, Zhengqi Wen +10
In the current era of Artificial Intelligence Generated Content (AIGC), a Low-Rank Adaptation (LoRA) method has emerged. It uses a plugin-based approach to learn new knowledge with…
A Noval Feature via Color Quantisation for Fake Audio Detection
Zhiyong Wang, Xiaopeng Wang, Yuankun Xie +9
In the field of deepfake detection, previous studies focus on using reconstruction or mask and prediction methods to train pre-trained models, which are then transferred to fake au…
Codecfake: An Initial Dataset for Detecting LLM-based Deepfake Audio
Yi Lu, Yuankun Xie, Ruibo Fu +9
With the proliferation of Large Language Model (LLM) based deepfake audio, there is an urgent need for effective detection methods. Previous deepfake audio generation methods typic…
Genuine-Focused Learning using Mask AutoEncoder for Generalized Fake Audio Detection
Xiaopeng Wang, Ruibo Fu, Zhengqi Wen +9
The generalization of Fake Audio Detection (FAD) is critical due to the emergence of new spoofing techniques. Traditional FAD methods often focus solely on distinguishing between g…
PPPR: Portable Plug-in Prompt Refiner for Text to Audio Generation
Shuchen Shi, Ruibo Fu, Zhengqi Wen +10
Text-to-Audio (TTA) aims to generate audio that corresponds to the given text description, playing a crucial role in media production. The text descriptions in TTA datasets lack ri…
Generalized Fake Audio Detection via Deep Stable Learning
Zhiyong Wang, Ruibo Fu, Zhengqi Wen +9
Although current fake audio detection approaches have achieved remarkable success on specific datasets, they often fail when evaluated with datasets from different distributions. P…