2 citations · 6 across the 21 of their papers we have counts for
12 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…
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…
Does Current Deepfake Audio Detection Model Effectively Detect ALM-based Deepfake Audio?
Yuankun Xie, Chenxu Xiong, Xiaopeng Wang +9
Currently, Audio Language Models (ALMs) are rapidly advancing due to the developments in large language models and audio neural codecs. These ALMs have significantly lowered the ba…
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…
The Codecfake Dataset and Countermeasures for the Universally Detection of Deepfake Audio
Yuankun Xie, Yi Lu, Ruibo Fu +9
With the proliferation of Audio Language Model (ALM) based deepfake audio, there is an urgent need for generalized detection methods. ALM-based deepfake audio currently exhibits wi…