24 citations · 32 across the 23 of their papers we have counts for
24 papers
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…
PSA-MF: Personality-Sentiment Aligned Multi-Level Fusion for Multimodal Sentiment Analysis
Heng Xie, Kang Zhu, Zhengqi Wen +4
Multimodal sentiment analysis (MSA) is a research field that recognizes human sentiments by combining textual, visual, and audio modalities. The main challenge lies in integrating…
Debunk and Infer: Multimodal Fake News Detection via Diffusion-Generated Evidence and LLM Reasoning
Kaiying Yan, Moyang Liu, Yukun Liu +4
The rapid spread of fake news across multimedia platforms presents serious challenges to information credibility. In this paper, we propose a Debunk-and-Infer framework for Fake Ne…
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…
MER 2025: When Affective Computing Meets Large Language Models
Zheng Lian, Rui Liu, Kele Xu +15
MER2025 is the third year of our MER series of challenges, aiming to bring together researchers in the affective computing community to explore emerging trends and future direction…
Deconfounded Reasoning for Multimodal Fake News Detection via Causal Intervention
Moyang Liu, Kaiying Yan, Yukun Liu +4
The rapid growth of social media has led to the widespread dissemination of fake news across multiple content forms, including text, images, audio, and video. Traditional unimodal…
Exploring Modality Disruption in Multimodal Fake News Detection
Moyang Liu, Kaiying Yan, Yukun Liu +4
The rapid growth of social media has led to the widespread dissemination of fake news across multiple content forms, including text, images, audio, and video. Compared to unimodal…
MTPareto: A MultiModal Targeted Pareto Framework for Fake News Detection
Kaiying Yan, Moyang Liu, Yukun Liu +5
Multimodal fake news detection is essential for maintaining the authenticity of Internet multimedia information. Significant differences in form and content of multimodal informati…
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…
Multimodal Diffusion Transformer with Memory Bank for Scalable Long-Duration Talking Video Generation
Haojie Zhang, Zhihao Liang, Ruibo Fu +5
Long-duration talking video synthesis faces enduring challenges in achieving high video quality, portrait consistency, temporal coherence, and computational efficiency. As video le…
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…
Exploring the Role of Audio in Multimodal Misinformation Detection
Moyang Liu, Yukun Liu, Ruibo Fu +4
With the rapid development of deepfake technology, especially the deep audio fake technology, misinformation detection on the social media scene meets a great challenge. Social med…
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…
ASRRL-TTS: Agile Speaker Representation Reinforcement Learning for Text-to-Speech Speaker Adaptation
Ruibo Fu, Xin Qi, Zhengqi Wen +10
Speaker adaptation, which involves cloning voices from unseen speakers in the Text-to-Speech task, has garnered significant interest due to its numerous applications in multi-media…
MDPE: A Multimodal Deception Dataset with Personality and Emotional Characteristics
Cong Cai, Shan Liang, Xuefei Liu +11
Deception detection has garnered increasing attention in recent years due to the significant growth of digital media and heightened ethical and security concerns. It has been exten…
MINT: a Multi-modal Image and Narrative Text Dubbing Dataset for Foley Audio Content Planning and Generation
Ruibo Fu, Shuchen Shi, Hongming Guo +12
Foley audio, critical for enhancing the immersive experience in multimedia content, faces significant challenges in the AI-generated content (AIGC) landscape. Despite advancements…
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…
TSNAT: Two-Step Non-Autoregressvie Transformer Models for Speech Recognition
Zhengkun Tian, Jiangyan Yi, Jianhua Tao +4
The autoregressive (AR) models, such as attention-based encoder-decoder models and RNN-Transducer, have achieved great success in speech recognition. They predict the output sequen…
Deep Attention Fusion Feature for Speech Separation with End-to-End Post-filter Method
Cunhang Fan, Jianhua Tao, Bin Liu +3
In this paper, we propose an end-to-end post-filter method with deep attention fusion features for monaural speaker-independent speech separation. At first, a time-frequency domain…