Create app.py

app.py

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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()