initial commit

app.py

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+import os
+import time
+import psutil
+import numpy as np
+import gradio as gr
+from resemblyzer import VoiceEncoder, preprocess_wav
+
+# Initialize the VoiceEncoder
+encoder = VoiceEncoder()
+
+def analyze_voice_similarity(audio_file1, audio_file2):
+    start_time = time.time()  # Record start time
+    
+    # Get current process information
+    process = psutil.Process(os.getpid())
+    
+    # Preprocess audio files
+    try:
+        wav1 = preprocess_wav(audio_file1)
+        wav2 = preprocess_wav(audio_file2)
+    except Exception as e:
+        return f"Error processing audio files: {str(e)}"
+    
+    # Extract speaker embeddings
+    embed1 = encoder.embed_utterance(wav1)
+    embed2 = encoder.embed_utterance(wav2)
+    
+    # Calculate cosine similarity between embeddings
+    similarity = np.dot(embed1, embed2) / (np.linalg.norm(embed1) * np.linalg.norm(embed2))
+    
+    # Determine if voices are from the same source
+    result = "SAME PERSON" if similarity >= 0.80 else "DIFFERENT PEOPLE"
+    
+    # Get memory usage
+    memory_usage = process.memory_info().rss / (1024 * 1024)  # in MB
+    
+    # Calculate execution time
+    execution_time = time.time() - start_time
+    
+    # Format the output
+    output = f"""
+### Voice Similarity Analysis Results
+
+**Similarity Score**: {similarity:.4f}
+**Conclusion**: {result}
+
+### Performance Metrics
+**Memory Usage**: {memory_usage:.2f} MB
+**Execution Time**: {execution_time:.4f} seconds
+    """
+    
+    return output
+
+# Create Gradio interface
+with gr.Blocks(title="Voice Similarity Analyzer") as demo:
+    gr.Markdown("# 🎤 Voice Similarity Analyzer")
+    gr.Markdown("Upload two audio files to check if they're from the same person. A similarity score >= 0.80 indicates the same speaker.")
+    
+    with gr.Row():
+        with gr.Column():
+            audio_input1 = gr.Audio(label="Voice Sample 1", type="filepath")
+        with gr.Column():
+            audio_input2 = gr.Audio(label="Voice Sample 2", type="filepath")
+    
+    analyze_button = gr.Button("Analyze Voice Similarity", variant="primary")
+    output_text = gr.Markdown(label="Results")
+    
+    analyze_button.click(
+        fn=analyze_voice_similarity,
+        inputs=[audio_input1, audio_input2],
+        outputs=output_text
+    )
+    
+    gr.Markdown("""
+    ## How It Works
+    1. Upload two voice recordings
+    2. Click "Analyze Voice Similarity"
+    3. The app will extract voice embeddings using Resemblyzer
+    4. The similarity score is calculated using cosine similarity
+    5. A score >= 0.80 indicates the same speaker
+
+    ## Performance Metrics
+    - Memory usage shows how much RAM is being used
+    - Execution time measures how long the comparison takes
+    """)
+
+# Launch the app
+if __name__ == "__main__":
+    demo.launch()

requirements.txt

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+gradio
+resemblyzer
+numpy
+psutil