Search Results for author:
Found 2 papers, 1 papers with code
DiffS2UT: A Semantic Preserving Diffusion Model for Textless Direct Speech-to-Speech Translation
While Diffusion Generative Models have achieved great success on image generation tasks, how to efficiently and effectively incorporate them into speech generation especially translation tasks remains a non-trivial problem.
Empowering Diffusion Models on the Embedding Space for Text Generation
Diffusion models have achieved state-of-the-art synthesis quality on both visual and audio tasks, and recent works further adapt them to textual data by diffusing on the embedding space.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
