Update app.py

app.py

@@ -1,7 +1,38 @@
 import gradio as gr
+import torch
+import torchaudio
+from speechbrain.inference.enhancement import SpectralMaskEnhancement
 
-def greet(name):
-    return "Hello " + name + "!!"
+# Load the MetricGAN model
+enhance_model = SpectralMaskEnhancement.from_hparams(
+    source="speechbrain/metricgan-plus-voicebank",
+    savedir="tmpdir_metricgan",
+)
 
-demo = gr.Interface(fn=greet, inputs="text", outputs="text")
-demo.launch()
+# Define a function to enhance speech
+def enhance_speech(audio):
+    # Load the audio and add fake batch dimension
+    noisy = enhance_model.load_audio(audio).unsqueeze(0)
+    
+    # Add relative length tensor (assuming full length)
+    lengths = torch.tensor([1.])
+    
+    # Enhance the audio
+    enhanced = enhance_model.enhance_batch(noisy, lengths)
+    
+    # Save enhanced audio to a temporary file
+    output_path = "enhanced.wav"
+    torchaudio.save(output_path, enhanced.cpu(), 16000)
+    return output_path
+
+# Set up the Gradio interface
+iface = gr.Interface(
+    fn=enhance_speech,
+    inputs=gr.Audio(type="filepath"),  # Removed 'source' argument
+    outputs=gr.Audio(type="filepath"),
+    title="Speech Enhancement",
+    description="Upload a noisy audio file to enhance it using MetricGAN."
+)
+
+# Launch the Gradio interface
+iface.launch()