File size: 2,055 Bytes
d054c06
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
---
license: apache-2.0
language:
- en
pipeline_tag: audio-to-audio
---

# Regularized Schrödinger Bridge (RSB) via Distortion-Perception Perturbation for High-Fidelity Speech Enhancement
[![License](https://img.shields.io/badge/license-Apache%202.0-blue.svg)](LICENSE)

Regularized Schrödinger Bridge (RSB) is a generative speech enhancement approach that reconciles fidelity and realism while mitigating exposure bias. RSB regularizes training with a Distortion-Perception Perturbation that constructs time-varying targets by interpolating between clean speech and posterior-mean estimates, and trains the network on perturbed intermediate states to correct toward the ground truth progressively. Consequently, such perturbation simulates inference-time prediction errors, mitigating the training–inference mismatch and thereby reducing exposure bias. Furthermore, it also injects posterior-mean estimates as fidelity-preserving guidance, facilitating reconstruction fidelity. 

- Official PyTorch implementation of the paper:  
[Regularized Schrödinger Bridge via Distortion-Perception Perturbation for High-Fidelity Speech Enhancement]()
- **Links**: Paper | [Audio Demo](https://yorch233.github.io/RSB/) | [Online Demo](https://huggingface.co/spaces/Yorch233/RSB) | [Github](https://github.com/Yorch233/RSB) | [Huggingface](https://huggingface.co/Yorch233/RSB)

<img src="https://github.com/Yorch233/RSB/raw/main/asset/RSB_schematic.png" width="600" />

#### Pretrained Model Download
We have publicly released a checkpoint of MISB's generative model, which is based the `ncsnpp_base` architecture and was trained on the `Voicebank+Demand` dataset.

There are two ways to download:

+ Download via `CLI`
```Bash
python -m cli.download_pretrained_model
```

+ Download via `Google Drive`. 
Download the folder from [Google Drive](https://drive.google.com/drive/folders/1b5wI-DIvq3yyLH_PKJPeb3d8VwxfwYIR?usp=sharing) and place it in the `pretrained_models/` directory.

## License

This project is licensed under the [Apache License 2.0](LICENSE).