The Automated Transcription System is a Python-based application that leverages OpenAI's Whisper model to transcribe audio and video files in real time. It features a user-friendly GUI built with Tkinter and automatically monitors a selected folder for new media files, transcribing them upon detection.
- Real-time Transcription: Watches a folder for new audio/video files and transcribes them automatically.
- GUI Interface: Provides an intuitive interface for selecting folders and managing transcriptions.
- Whisper Model Integration: Uses OpenAI's Whisper model for high-quality speech-to-text conversion.
- Multi-Format Support: Supports common media file types including MP3, WAV, MP4, MKV, and more.
- Efficient Processing: Avoids duplicate processing of already transcribed files.
Ensure you have Python installed (Python 3.8+ recommended) and install the required dependencies:
pip install torch whisper tkinter watchdogClone this repository:
git clone [https://github.com/yourusername/transcription-system.git](https://github.com/yourusername/transcription-system.git)Navigate to the project directory:
cd transcription-systemRun the application:
python realtime_transcriber.py- Select Folder: Choose a directory where media files will be monitored.
- Start Monitoring: Click the "Start Monitoring" button to begin automatic transcription.
- View Logs: The GUI displays updates on detected files and transcription progress.
- Stop Monitoring: Click "Stop Monitoring" to stop the process.
- Audio: MP3, WAV, AAC, M4A
- Video: MP4, MKV, MOV, FLV
- Support for more languages.
- Cloud storage integration for transcriptions.
- Live audio recording and transcription.
- This project is licensed under the MIT License - see the LICENSE file for details.
OpenAI for the Whisper model. Python community for libraries like Tkinter and Watchdog. Contribute Feel free to submit issues or pull requests to improve this project!
For any questions or suggestions, reach out via GitHub issues.