Update app.py

app.py

@@ -1,38 +0,0 @@
-import gradio as gr
-import torch
-import torchaudio
-#from speechbrain.inference.enhancement import SpectralMaskEnhancement
-
-# Load the MetricGAN model
-enhance_model = SpectralMaskEnhancement.from_hparams(
-    source="speechbrain/metricgan-plus-voicebank",
-    savedir="tmpdir_metricgan",
-)
-
-# 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()