Audio Transcription Tool Python, AI

```python
import speech_recognition as sr
import os

def transcribe_audio(audio_file_path):
    """
    Transcribes an audio file using Google Web Speech API.

    Args:
        audio_file_path (str): The path to the audio file.

    Returns:
        str: The transcribed text, or None if an error occurred.
    """
    r = sr.Recognizer()
    with sr.AudioFile(audio_file_path) as source:
        audio = r.record(source)  # Read the entire audio file.

    try:
        text = r.recognize_google(audio)
        return text
    except sr.UnknownValueError:
        print("Google Speech Recognition could not understand audio")
        return None
    except sr.RequestError as e:
        print(f"Could not request results from Google Speech Recognition service; {e}")
        return None


def transcribe_audio_using_whisper(audio_file_path, model_name="base"):  # added whisper implementation
    """
    Transcribes an audio file using OpenAI's Whisper model.

    Args:
        audio_file_path (str): The path to the audio file.
        model_name (str): The name of the Whisper model to use (e.g., "base", "small", "medium", "large").

    Returns:
        str: The transcribed text, or None if an error occurred.
    """
    try:
        import whisper
    except ImportError:
        print("Please install the 'whisper' library: pip install openai-whisper")
        return None

    try:
        model = whisper.load_model(model_name)
        result = model.transcribe(audio_file_path)
        return result["text"]
    except Exception as e:
        print(f"Error during Whisper transcription: {e}")
        return None



def main():
    """
    Main function to handle audio transcription.
    """
    audio_file = input("Enter the path to the audio file: ")

    if not os.path.exists(audio_file):
        print("Error: Audio file not found.")
        return

    transcription_method = input("Choose transcription method (google/whisper): ").lower()

    if transcription_method == "google":
        transcribed_text = transcribe_audio(audio_file)
    elif transcription_method == "whisper":
        model_size = input("Enter Whisper model size (base, small, medium, large): ").lower()
        transcribed_text = transcribe_audio_using_whisper(audio_file, model_size)
    else:
        print("Invalid transcription method.  Choose google or whisper.")
        return

    if transcribed_text:
        print("\nTranscription:")
        print(transcribed_text)

        # Optionally save the transcription to a file:
        save_to_file = input("Save transcription to file? (y/n): ").lower()
        if save_to_file == 'y':
            output_file = input("Enter the output file name: ")
            try:
                with open(output_file, "w") as f:
                    f.write(transcribed_text)
                print(f"Transcription saved to {output_file}")
            except Exception as e:
                print(f"Error saving to file: {e}")
    else:
        print("Transcription failed.")

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