whisper/farsi_transcriber

Farsi Transcriber

A desktop application for transcribing Farsi audio and video files using OpenAI's Whisper model.

Features

• 🎙️ Transcribe audio files (MP3, WAV, M4A, FLAC, OGG, etc.)
• 🎬 Extract audio from video files (MP4, MKV, MOV, WebM, AVI, etc.)
• 🇮🇷 High-accuracy Farsi transcription
• ⏱️ Word-level timestamps
• 📤 Export to multiple formats (TXT, SRT, JSON)
• 💻 Clean PyQt6-based GUI

System Requirements

• Python 3.8+
• ffmpeg (for audio/video processing)
• 8GB+ RAM recommended (for high-accuracy model)

Install ffmpeg

Ubuntu/Debian:

sudo apt update && sudo apt install ffmpeg

macOS (Homebrew):

brew install ffmpeg

Windows (Chocolatey):

choco install ffmpeg

Installation

1. Clone the repository
2. Create a virtual environment:

python3 -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

3. Install dependencies:

pip install -r requirements.txt

4. Run the application:

python main.py

Usage

GUI Application

python main.py

Then:

1. Click "Select File" to choose an audio or video file
2. Click "Transcribe" and wait for processing
3. View results with timestamps
4. Export to your preferred format

Command Line (Coming Soon)

python -m farsi_transcriber --input audio.mp3 --output transcription.srt

Model Information

This application uses OpenAI's Whisper model optimized for Farsi:

• Model: medium or large (configurable)
• Accuracy: Optimized for Persian language
• Processing: Local processing (no cloud required)

Project Structure

farsi_transcriber/
├── ui/               # PyQt6 UI components
├── models/           # Whisper model management
├── utils/            # Utility functions
├── main.py           # Application entry point
├── requirements.txt  # Python dependencies
└── README.md         # This file

Development

Running Tests

pytest tests/

Code Style

black .
flake8 .
isort .

License

MIT License - See LICENSE file for details

Contributing

This is a personal project, but feel free to fork and modify for your needs!