Sepformer Wham Enhancement No1

--- language: "en" thumbnail: tags: - audio-to-audio - Speech Enhancement - WHAM! - SepFormer - Transformer - pytorch - speechbrain license: "apache-2.0" metrics: - SI-SNR - PESQ --- <iframe src="https://ghbtns.com/github-btn.html?user=speechbrain&repo=speechbrain&type=star&count=true&size=large&v=2" frameborder="0" scrolling="0" width="170" height="30" title="GitHub"></iframe> <br/><br/> # SepFormer trained on WHAM! for speech enhancement (8k sampling frequency) This repository provides all the necessary tools to perform speech enhancement (denoising) with a [SepFormer](https://arxiv.org/abs/2010.13154v2) model, implemented with SpeechBrain, and pretrained on [WHAM!](http://wham.whisper.ai/) dataset with 8k sampling frequency, which is basically a version of WSJ0-Mix dataset with environmental noise and reverberation in 8k. For a better experience we encourage you to learn more about [SpeechBrain](https://speechbrain.github.io). The given model performance is 14.35 dB SI-SNR on the test set of WHAM! dataset. | Release | Test-Set SI-SNR | Test-Set PESQ | |:-------------:|:--------------:|:--------------:| | 01-12-21 | 14.35 | 3.07 | ## Install SpeechBrain First of all, please install SpeechBrain with the following command: ``` pip install speechbrain ``` Please notice that we encourage you to read our tutorials and learn more about [SpeechBrain](https://speechbrain.github.io). ### Perform speech enhancement on your own audio file ```python from speechbrain.inference.separation import SepformerSeparation as separator import torchaudio model = separator.from_hparams(source="speechbrain/sepformer-wham-enhancement", savedir='pretrained_models/sepformer-wham-enhancement') # for custom file, change path est_sources = model.separate_file(path='speechbrain/sepformer-wham-enhancement/example_wham.wav') torchaudio.save("enhanced_wham.wav", est_sources[:, :, 0].detach().cpu(), 8000) ``` ### Inference on GPU To perform inference on the GPU, add `run_opts={"device":"cuda"}` when calling the `from_hparams` method. ### Training The training script is currently being worked on an ongoing pull-request. We will update the model card as soon as the PR is merged. You can find our training results (models, logs, etc) [here](https://drive.google.com/drive/folders/1bbQvaiN-R79M697NnekA7Rr0jIYtO6e3). ### Limitations The SpeechBrain team does not provide any wa...

Source context: 0 downloads · 0 likes · Pipeline audio-to-audio · Library speechbrain · Repo loveisgone/sepformer-wham-enhancement-no1