```python
from audio_processing import AudioRecorder
from accent_conversion import AccentConverter
from whisper_integration import WhisperTranscriber
import os
import time

def main():
    # Initialize components
    recorder = AudioRecorder()
    converter = AccentConverter()
    transcriber = WhisperTranscriber(model_size="base")
    
    print("Accentify - Real-Time Accent Conversion System")
    print("Available accents: american, british, australian, indian")
    
    try:
        while True:
            print("\nMenu:")
            print("1. Record and transcribe")
            print("2. Convert accent of existing audio")
            print("3. Exit")
            
            choice = input("Enter your choice (1-3): ")
            
            if choice == "1":
                # Record audio
                output_file = recorder.record_and_save(duration=5)
                
                # Detect language/transcribe with Whisper
                print("\nTranscribing with Whisper...")
                whisper_result = transcriber.transcribe_audio(output_file)
                print(f"Detected language: {whisper_result['language']}")
                print(f"Transcription: {whisper_result['text']}")
                
                # Convert accent
                target_accent = input("Enter target accent (american/british/australian/indian): ").lower()
                if target_accent not in converter.models:
                    print("Invalid accent. Using 'american' as default.")
                    target_accent = "american"
                
                output_audio, converted_text = converter.convert_accent(
                    output_file, 
                    source_accent="american",  # In real app, detect source accent
                    target_accent=target_accent
                )
                
                print(f"\nConverted text: {converted_text}")
                print(f"Saved converted audio to: {output_audio}")
            elif choice == "2":
                audio_path = input("Enter path to audio file: ")
                if not os.path.exists(audio_path):
                    print("File not found!")
                    continue
                    
                # First detect source accent
                print("Detecting source accent...")
                source_accent = converter.detect_accent(audio_path)
                print(f"Detected accent: {source_accent}")
                
                target_accent = input("Enter target accent (american/british/australian/indian): ").lower()
                if target_accent not in converter.models:
                    print("Invalid accent. Using 'american' as default.")
                    target_accent = "american"
                
                output_audio, converted_text = converter.convert_accent(
                    audio_path, 
                    source_accent=source_accent,
                    target_accent=target_accent
                )
print(f"\nConverted text: {converted_text}")
                print(f"Saved converted audio to: {output_audio}")
                
            elif choice == "3":
                print("Exiting...")
                break
                
            else:
                print("Invalid choice. Please try again.")
                
    except KeyboardInterrupt:
        print("\nExiting...")

if __name__ == "__main__":
    main()
```

These Python files provide the backend functionality needed for the accent conversion system:
1. `audio_processing.py` - Handles audio recording using sounddevice
2. `accent_conversion.py` - Uses wav2vec2 for speech recognition and gTTS for text-to-speech
3. `whisper_integration.py` - Provides Whisper AI transcription capabilities
4. `requirements.txt` - Lists all required Python packages
5. `main.py` - Demonstrates the complete workflow

The system can:
- Record audio using the microphone
- Transcribe speech using Whisper or wav2vec2
- Convert text to speech with different accents using gTTS
- Save audio files and manage temporary files
- Handle different input/output formats

To use these files, users should:
1. Install the requirements: `pip install -r requirements.txt`
2. Run the main script: `python main.py`
3. Follow the interactive menu to record and convert speech

Note: For production use, you would need to:
- Handle API keys securely
- Add error handling
- Optimize model loading
- Add web server integration (FastAPI/Flask)
- Implement proper accent detection
- Add more sophisticated accent conversion techniques
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___METADATA_END___