Dasheng Denoiser

Official PyTorch inference code for the Interspeech 2025 paper:
Efficient Speech Enhancement via Embeddings from Pre-trained Generative Audioencoders

Installation and Usage

uv pip install transformers torch torchaudio einops

import torch
import torchaudio
from transformers import AutoModel
model = AutoModel.from_pretrained("mispeech/dasheng-denoiser",  trust_remote_code=True)
model.eval()
# Load audio file (only 16kHz supported!)
audio, sr = torchaudio.load("path/to/audio.wav")
with torch.no_grad(), torch.autocast(device_type='cuda'):
    enhanced = model(audio)
torchaudio.save("enhanced_audio.wav", enhanced, sr)

Acknowledgements

We referred to Dasheng and Vocos to implement this.

Citation

@inproceedings{xingwei2025dashengdenoiser,
  title={Efficient Speech Enhancement via Embeddings from Pre-trained Generative Audioencoders},
  author={Xingwei Sun, Heinrich Dinkel, Yadong Niu, Linzhang Wang, Junbo Zhang, Jian Luan},
  booktitle={Interspeech 2025},
  year={2025}
}