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Variance-Preserving-Based Interpolation Diffusion Models for Speech Enhancement
- Publication Year :
- 2023
-
Abstract
- The goal of this study is to implement diffusion models for speech enhancement (SE). The first step is to emphasize the theoretical foundation of variance-preserving (VP)-based interpolation diffusion under continuous conditions. Subsequently, we present a more concise framework that encapsulates both the VP- and variance-exploding (VE)-based interpolation diffusion methods. We demonstrate that these two methods are special cases of the proposed framework. Additionally, we provide a practical example of VP-based interpolation diffusion for the SE task. To improve performance and ease model training, we analyze the common difficulties encountered in diffusion models and suggest amenable hyper-parameters. Finally, we evaluate our model against several methods using a public benchmark to showcase the effectiveness of our approach
Details
- Database :
- arXiv
- Publication Type :
- Report
- Accession number :
- edsarx.2306.08527
- Document Type :
- Working Paper