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| import torch | |
| import torchaudio | |
| from speechbrain.pretrained import SpectralMaskEnhancement | |
| import gradio as gr | |
| enhance_model = SpectralMaskEnhancement.from_hparams( | |
| source="speechbrain/metricgan-plus-voicebank", | |
| savedir="pretrained_models/metricgan-plus-voicebank", | |
| ) | |
| def speechbrain(aud): | |
| # Load and add fake batch dimension | |
| noisy = enhance_model.load_audio( | |
| aud.name | |
| ).unsqueeze(0) | |
| enhanced = enhance_model.enhance_batch(noisy, lengths=torch.tensor([1.])) | |
| torchaudio.save('enhanced.wav', enhanced.cpu(), 16000) | |
| return 'enhanced.wav' | |
| inputs = gr.inputs.Audio(label="Input Audio", type="file") | |
| outputs = gr.outputs.Audio(label="Output Audio", type="file") | |
| title = "Speechbrain Speech Enhancement" | |
| 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." | |
| 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>" | |
| examples = [ | |
| ['samples_audio_samples_example_fr.wav'] | |
| ] | |
| gr.Interface(speechbrain, inputs, outputs, title=title, description=description, article=article, examples=examples).launch() |