4 papers
Spiking Vocos: An Energy-Efficient Neural Vocoder
Yukun Chen, Zhaoxi Mu, Andong Li +2
Despite the remarkable progress in the synthesis speed and fidelity of neural vocoders, their high energy consumption remains a critical barrier to practical deployment on computat…
From Continuous to Discrete: Cross-Domain Collaborative General Speech Enhancement via Hierarchical Language Models
Zhaoxi Mu, Rilin Chen, Andong Li +3
This paper introduces OmniGSE, a novel general speech enhancement (GSE) framework designed to mitigate the diverse distortions that speech signals encounter in real-world scenarios…
SepALM: Audio Language Models Are Error Correctors for Robust Speech Separation
Zhaoxi Mu, Xinyu Yang, Gang Wang
While contemporary speech separation technologies adeptly process lengthy mixed audio waveforms, they are frequently challenged by the intricacies of real-world environments, inclu…
Separate in the Speech Chain: Cross-Modal Conditional Audio-Visual Target Speech Extraction
Zhaoxi Mu, Xinyu Yang
The integration of visual cues has revitalized the performance of the target speech extraction task, elevating it to the forefront of the field. Nevertheless, this multi-modal lear…