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README.md

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-license: apache-2.0
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+---
+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).