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Duplicate from akhaliq/speechbrain-speech-seperation

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Co-authored-by: AK <[email protected]>

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README.md ADDED
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+ ---
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+ title: Speechbrain-speech-seperation
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+ emoji: 👁
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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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+
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+ # Configuration
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+
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+ `title`: _string_
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+ Display title for the Space
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+
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+ `emoji`: _string_
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+ Space emoji (emoji-only character allowed)
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+
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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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+
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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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+
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+ `sdk`: _string_
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+ Can be either `gradio` or `streamlit`
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+
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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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+
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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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+
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+ `pinned`: _boolean_
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+ Whether the Space stays on top of your list.
app.py ADDED
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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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+
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+ model = separator.from_hparams(source="speechbrain/sepformer-wsj02mix", savedir='pretrained_models/sepformer-wsj02mix')
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+
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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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+
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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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+
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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()
requirements.txt ADDED
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+ speechbrain
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+ torchaudio
samples_audio_samples_test_mixture.wav ADDED
Binary file (66.2 kB). View file