3 papers
cs.LG2026
Corrective Forcing: Unified Post-Training for Diffusions and Flows in Generative Speech Enhancement
Qing Yao, Lijian Gao, Qirong Mao
Diffusion and flow models, as promising generative paradigms for speech enhancement, face a training--inference mismatch: training uses analytical path states, whereas inference re…
cs.SD2025
Keyword Mamba: Spoken Keyword Spotting with State Space Models
Hanyu Ding, Wenlong Dong, Qirong Mao
Keyword spotting (KWS) is an essential task in speech processing. It is widely used in voice assistants and smart devices. Deep learning models like CNNs, RNNs, and Transformers ha…
eess.AS2025
EDSep: An Effective Diffusion-Based Method for Speech Source Separation
Jinwei Dong, Xinsheng Wang, Qirong Mao
Generative models have attracted considerable attention for speech separation tasks, and among these, diffusion-based methods are being explored. Despite the notable success of dif…