This is SUSTech Audio Intelligence Lab (SAIL) 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), Ph.D. students, Post-docs, Research Associates (研究助理), and visiting students. Our group also warmly welcomes undergraduate students. If you are interested in joining us, please send the Prof. Wang your CV, or visit Prof. Wang's office in person.
News
- [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 3D Binaural Localization of Overlapping Speakers" are accpeted to Interspeech 2025.
- [05/2025] - Our paper "Unsupervised Blind Speech Separation with A Diffusion Prior" is accpeted to ICML 2025.
- [04/2025] - Our paper "An End-to-End Integration of Speech Separation and Recognition with Self-Supervised Learning Representation" is accpeted to Computer Speech & Language.
- [03/2025] - Our paper "SuperM2M: Supervised and Mixture-to-Mixture Co-Learning for Speech Enhancement and Noise-Robust ASR" is accpeted 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.