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Duplicate from akhaliq/speechbrain-speech-seperation
Browse filesCo-authored-by: AK <akhaliq@users.noreply.huggingface.co>
- .gitattributes +27 -0
- README.md +38 -0
- app.py +25 -0
- requirements.txt +2 -0
- samples_audio_samples_test_mixture.wav +0 -0
.gitattributes
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README.md
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---
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title: Speechbrain-speech-seperation
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emoji: π
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colorFrom: red
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colorTo: gray
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sdk: gradio
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app_file: app.py
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pinned: false
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duplicated_from: akhaliq/speechbrain-speech-seperation
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---
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# Configuration
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`title`: _string_
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Display title for the Space
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`emoji`: _string_
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Space emoji (emoji-only character allowed)
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`colorFrom`: _string_
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Color for Thumbnail gradient (red, yellow, green, blue, indigo, purple, pink, gray)
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`colorTo`: _string_
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Color for Thumbnail gradient (red, yellow, green, blue, indigo, purple, pink, gray)
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`sdk`: _string_
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Can be either `gradio` or `streamlit`
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`sdk_version` : _string_
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Only applicable for `streamlit` SDK.
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See [doc](https://hf.co/docs/hub/spaces) for more info on supported versions.
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`app_file`: _string_
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Path to your main application file (which contains either `gradio` or `streamlit` Python code).
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Path is relative to the root of the repository.
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`pinned`: _boolean_
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Whether the Space stays on top of your list.
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app.py
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from speechbrain.pretrained import SepformerSeparation as separator
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import torchaudio
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import gradio as gr
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model = separator.from_hparams(source="speechbrain/sepformer-wsj02mix", savedir='pretrained_models/sepformer-wsj02mix')
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def speechbrain(aud):
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est_sources = model.separate_file(path=aud.name)
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torchaudio.save("source1hat.wav", est_sources[:, :, 0].detach().cpu(), 8000)
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torchaudio.save("source2hat.wav", est_sources[:, :, 1].detach().cpu(), 8000)
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return "source1hat.wav", "source2hat.wav"
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inputs = gr.inputs.Audio(label="Input Audio", type="file")
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outputs = [
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gr.outputs.Audio(label="Output Audio One", type="file"),
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gr.outputs.Audio(label="Output Audio Two", type="file")
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]
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title = "Speech Seperation"
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description = "Gradio demo for Speech Seperation by SpeechBrain. To use it, simply upload your audio, or click one of the examples to load them. Read more at the links below."
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article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2010.13154' target='_blank'>Attention is All You Need in Speech Separation</a> | <a href='https://github.com/speechbrain/speechbrain/tree/develop/recipes/WSJ0Mix/separation' '_blank'>Github Repo</a></p>"
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examples = [
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['samples_audio_samples_test_mixture.wav']
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]
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gr.Interface(speechbrain, inputs, outputs, title=title, description=description, article=article, examples=examples).launch()
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requirements.txt
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speechbrain
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torchaudio
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samples_audio_samples_test_mixture.wav
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Binary file (66.2 kB). View file
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