🔊 Real-Time-Audio-Recorder-and-Transcriber-using-Whisper-AI

This project is an interactive desktop application that allows users to record audio in real-time, save the recordings, and transcribe the audio to text using the Whisper AI model. The user-friendly interface is built with Tkinter, making it easy to start and stop recordings and generate transcriptions with just a few clicks.

This Python-based GUI application allows you to record audio, save it as a .wav file, and transcribe it into text using OpenAI's Whisper model. Built with tkinter, it features buttons to start/stop recording and transcribe audio, saving the recording as output.wav and the transcription as transcription.txt.

🔥 Features

1. Real-Time Audio Recording: Users can start and stop audio recordings with the click of a button. Audio is captured using PyAudio, ensuring high-quality recordings.

2. Audio File Management: Recorded audio is saved in WAV format for compatibility and quality retention. Automatic file saving upon stopping the recording.

3. AI-Powered Transcription: Uses Whisper, an advanced speech-to-text model, to transcribe recorded audio. Transcription results are saved to a text file for easy access and further use.

4. User-Friendly Interface: Built with Tkinter, the application provides a simple, clean, and responsive interface. Buttons are styled for ease of use and accessibility.

🛠️ Installation

1. Fork this repository: Fork the CowTheGreat/Real-Time-Audio-Recorder-and-Transcriber-using-Whisper-AI repository. Follow these instructions on how to fork a repository

2. Clone the project: git clone [email protected]:your-username/Real-Time-Audio-Recorder-and-Transcriber-using-Whisper-AI

3. Required downloads:

  cd Real-Time-Audio-Recorder-and-Transcriber-using-Whisper-AI
  pip install -r requirements.txt

4. Alternative ways to download the dependencies:

• To run, install Python 3.8+ and required packages (pyaudio and whisper) using

pip install pyaudio whisper

• Whisper downloads its models on the first run; ensure an active internet connection. Customize the Whisper model by modifying whisper.load_model("small") in the code (options: tiny, base, small, medium, large).

• For more on Whisper, visit https://github.com/openai/whisper.

5. Running the project: Run the application with :

   python ui.py

🚀 How It Works

• Start Recording: Click the "Start Recording" button to begin capturing audio. The button will be disabled while recording is in progress.
• Stop Recording: Click the "Stop Recording" button to end the audio capture. The application saves the audio to a file and enables the transcription feature.
• Transcribe Audio: Click the "Transcribe" button to convert the recorded audio into text. The transcribed text is saved to a file named transcription.txt.

🙌 Contributing

Contributions are always welcome! Whether you want to report an issue, suggest a feature, or submit a pull request, your input is greatly appreciated.

🧑💻 Contributor's Guide

Welcome, contributors! Here's how you can help improve this project:

Getting Started

1. Fork the Repository: Click "Fork" at the top right of the GitHub repository page.
2. Clone Your Fork:

git clone https://github.com/your-username/Real-Time-Audio-Recorder-and-Transcriber-using-Whisper-AI.git

3. Create a Feature Branch:

git checkout -b feature/your-feature-name

Coding Guidelines

• Follow PEP 8 style guidelines for Python code.
• Add comments for complex logic.
• Write tests for new features (if applicable). -Test changes locally before submitting a pull request.

Pull Request Process

• Ensure your branch is updated with the latest main branch.
• Submit a PR to the original repository's main branch.
• Describe your changes clearly in the PR description.
• Address any review feedback promptly.

📚 Examples & Tutorials

Changing the Whisper Model Size

Modify ui.py to use a different model (e.g., "medium"):

model = whisper.load_model("medium")  # Instead of "small"

Customizing File Save Paths

Change where files are saved by editing these lines in ui.py:

# For audio files
wf = wave.open("custom_folder/output.wav", 'wb')

# For transcriptions
with open("custom_folder/transcription.txt", "w") as f:

❓ FAQ (Troubleshooting)

Q: I get errors installing PyAudio on Windows. A: Try installing using pre-built binaries:

pip install pipwin
pipwin install pyaudio

Q: Whisper fails to download models. A: Ensure you have an active internet connection. If blocked by a firewall, manually download the model from OpenAI's repository and place it in ~/.cache/whisper/.

Q: "Permission denied" when saving files. A: Run the app as administrator/root, or change the save directory to a location with write permissions.

🛡️ Error-Handling Best Practices

• User Feedback: The GUI shows error messages in alerts instead of console logs.
• Exception Handling: Contributors should wrap risky operations in try-except blocks:

try:
    # Risky code
except Exception as e:
    messagebox.showerror("Error", str(e))

• Logging: Consider adding logging for debugging (PRs welcome!).

🚧 Future Features & Roadmap

Planned Features

• Real-time transcription while recording.
• Support for MP3 and other audio formats.
• Language selection for transcription.
• Progress bar during transcription.

In Progress

• GUI dark/light theme toggle (WIP by @contributor).

⭐️ Acknowledgements

A very big thanks to all the contributors for helping this project grow. Your efforts are greatly appreciated!