This is SUSTech Audio Intelligence Lab (SAIL, 南科大音频智能实验室) directed by Prof. Zhong-Qiu Wang in the Department of Computer Science and Engineering at Southern University of Science and Technology (SUSTech) in Shenzhen, China.
We are interested in broad speech/audio signal processing and artificial intelligence problems, aiming at building machine listening systems that can robustly perceive and understand speech/audio in reverberant environments with multiple concurrent sound sources. Our current research focuses on deep learning based approaches for speech enhancement, speaker separation, speech dereverberation and robust automatic speech recognition based on a single microphone or an array of microphones, targeting at solving the cocktail party problem.
Our group has openings for Master students (保研/考研) and Ph.D. students. If you are interested in joining us, please send Prof. Wang your CV, or visit Prof. Wang's office in person.
News
- [07/2025] - We rank third place in "DCASE2025 Challenge Task 4 - Spatial Semantic Segmentation of Sound Scenes". See our technical report for our solutions.
- [06/2025] - Our paper "Unsupervised Multi-Channel Speech Dereverberation via Diffusion" is accepted to ICML Workshop on Machine Learning for Audio, 2025.
- [05/2025] - Our papers "ARiSE: Auto-Regressive Multi-Channel Speech Enhancement", "Multi-Channel Acoustic Echo Cancellation Based on Direction-of-Arrival Estimation", and "AuralNet: Hierarchical Attention-based 3D Binaural Localization of Overlapping Speakers" are accepted to Interspeech 2025.
- [05/2025] - Our paper "Unsupervised Blind Speech Separation with A Diffusion Prior" is accepted to ICML 2025.
- [04/2025] - Our paper "An End-to-End Integration of Speech Separation and Recognition with Self-Supervised Learning Representation" is accepted to Computer Speech & Language.
- [03/2025] - Our paper "SuperM2M: Supervised and Mixture-to-Mixture Co-Learning for Speech Enhancement and Noise-Robust ASR" is accepted to Neural Networks.
- [12/2024] - Our paper "30+ Years of Source Separation Research: Achievements and Future Challenges" is accepted to ICASSP 2025.
- [08/2024] - Our paper "USDnet: Unsupervised Speech Dereverberation via Neural Forward Filtering" is accepted to IEEE/ACM TASLP.