7 citations · 24 across the 37 of their papers we have counts for
14 papers · 1 filter
Continual Audio Deepfake Detection via Universal Adversarial Perturbation
Wangjie Li, Lin Li, Qingyang Hong
The rapid advancement of speech synthesis and voice conversion technologies has raised significant security concerns in multimedia forensics. Although current detection models demo…
SyncVoice: Simple and Effective Automatic Video Dubbing with Vision-Augmented TTS
Kaidi Wang, Yi He, Wenhao Guan +9
Automatic video dubbing aims to generate high-fidelity speech that is temporally aligned with visual content. However, existing methods still suffer from limited speech naturalness…
XMUspeech Systems for the ASVspoof 5 Challenge
Wangjie Li, Xingjia Xie, Yishuang Li +5
In this paper, we present our submitted XMUspeech systems to the speech deepfake detection track of the ASVspoof 5 Challenge. Compared to previous challenges, the audio duration in…
Phoenix-VAD: Streaming Semantic Endpoint Detection for Full-Duplex Speech Interaction
Weijie Wu, Wenhao Guan, Kaidi Wang +6
Spoken dialogue models have significantly advanced intelligent human-computer interaction, yet they lack a plug-and-play full-duplex prediction module for semantic endpoint detecti…
MeanFlowSE: one-step generative speech enhancement via conditional mean flow
Duojia Li, Shenghui Lu, Hongchen Pan +3
Multistep inference is a bottleneck for real-time generative speech enhancement because flow- and diffusion-based systems learn an instantaneous velocity field and therefore rely o…
SuPseudo: A Pseudo-supervised Learning Method for Neural Speech Enhancement in Far-field Speech Recognition
Longjie Luo, Lin Li, Qingyang Hong
Due to the lack of target speech annotations in real-recorded far-field conversational datasets, speech enhancement (SE) models are typically trained on simulated data. However, th…
Pseudo Labels-based Neural Speech Enhancement for the AVSR Task in the MISP-Meeting Challenge
Longjie Luo, Shenghui Lu, Lin Li +1
This paper presents our system for the MISP-Meeting Challenge Track 2. The primary difficulty lies in the dataset, which contains strong background noise, reverberation, overlappin…
Cross-attention and Self-attention for Audio-visual Speaker Diarization in MISP-Meeting Challenge
Zhaoyang Li, Haodong Zhou, Longjie Luo +4
This paper presents the system developed for Task 1 of the Multi-modal Information-based Speech Processing (MISP) 2025 Challenge. We introduce CASA-Net, an embedding fusion method…
Speaker Diarization with Overlapping Community Detection Using Graph Attention Networks and Label Propagation Algorithm
Zhaoyang Li, Jie Wang, XiaoXiao Li +4
In speaker diarization, traditional clustering-based methods remain widely used in real-world applications. However, these methods struggle with the complex distribution of speaker…
ReFlow-VC: Zero-shot Voice Conversion Based on Rectified Flow and Speaker Feature Optimization
Pengyu Ren, Wenhao Guan, Kaidi Wang +3
In recent years, diffusion-based generative models have demonstrated remarkable performance in speech conversion, including Denoising Diffusion Probabilistic Models (DDPM) and othe…
A Two-Stage Hierarchical Deep Filtering Framework for Real-Time Speech Enhancement
Shenghui Lu, Hukai Huang, Jinanglong Yao +3
This paper proposes a model that integrates sub-band processing and deep filtering to fully exploit information from the target time-frequency (TF) bin and its surrounding TF bins…
DS-Codec: Dual-Stage Training with Mirror-to-NonMirror Architecture Switching for Speech Codec
Peijie Chen, Wenhao Guan, Kaidi Wang +4
Neural speech codecs are essential for advancing text-to-speech (TTS) systems. With the recent success of large language models in text generation, developing high-quality speech t…
Discl-VC: Disentangled Discrete Tokens and In-Context Learning for Controllable Zero-Shot Voice Conversion
Kaidi Wang, Wenhao Guan, Ziyue Jiang +5
Currently, zero-shot voice conversion systems are capable of synthesizing the voice of unseen speakers. However, most existing approaches struggle to accurately replicate the speak…
SlimSpeech: Lightweight and Efficient Text-to-Speech with Slim Rectified Flow
Kaidi Wang, Wenhao Guan, Shenghui Lu +3
Recently, flow matching based speech synthesis has significantly enhanced the quality of synthesized speech while reducing the number of inference steps. In this paper, we introduc…