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import torch |
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import torchaudio |
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from speechbrain.pretrained import SpectralMaskEnhancement |
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import gradio as gr |
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enhance_model = SpectralMaskEnhancement.from_hparams( |
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source="speechbrain/metricgan-plus-voicebank", |
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savedir="pretrained_models/metricgan-plus-voicebank", |
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) |
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def speechbrain(aud): |
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noisy = enhance_model.load_audio( |
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aud.name |
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).unsqueeze(0) |
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enhanced = enhance_model.enhance_batch(noisy, lengths=torch.tensor([1.])) |
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torchaudio.save('enhanced.wav', enhanced.cpu(), 16000) |
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return 'enhanced.wav' |
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inputs = gr.inputs.Audio(label="Input Audio", type="file") |
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outputs = gr.outputs.Audio(label="Output Audio", type="file") |
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title = "Speechbrain Speech Enhancement" |
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description = "Gradio demo for Speech enhancement with 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/2104.03538' target='_blank'>MetricGAN+: An Improved Version of MetricGAN for Speech Enhancement</a> | <a href='https://github.com/speechbrain/speechbrain' target='_blank'>Github Repo</a></p>" |
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examples = [ |
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['samples_audio_samples_example_fr.wav'] |
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] |
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gr.Interface(speechbrain, inputs, outputs, title=title, description=description, article=article, examples=examples).launch() |
