AutoTranscript GUI 🎙️

AutoTranscript is a powerful, GPU-accelerated subtitle generator built on top of OpenAI's Whisper model. It features both a command-line interface (CLI) and a beautiful CustomTkinter-based GUI for users who prefer a graphical workflow.

Supports:

• Languages such as: English, Chinese, Japanese, Korean.
• Local audio/video files.
• Translate or transcribe YouTube videos using only the link.
• Subtitle translation to English.
• OpenAI API (for higher quality translations) NOT AVAILABLE

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✨ Features

• 🖥️ Full-featured GUI with progress tracking, real-time logs.
• 📜 Generate .srt subtitle files from media files
• 🌍 Supports multilingual transcription and optional translation to English
• 🧠 Uses Faster-Whisper for fast GPU-accelerated transcription

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YOUTUBE TUTORIAL IN SPANISH

(https://www.youtube.com/watch?v=dB6D1i1BjXc)

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📸 GUI Preview

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🧩 Requirements

• Python
• NVIDIA GPU with CUDA (recommended)
• Visual C++ Redistributable 14

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Installation for Releases

• Extract the .rar file.
• Go to the app folder.
• At the top of the path bar, type cmd.
• In the console, type: pip install -r requirements.txt.
• Go back to the .bat file and run it.

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📦 Installation

git clone https://github.com/jjaruna/autoTranscriptGUI.git
cd autoTranscriptGUI
pip install -r requirements.txt

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🚀 Launch the GUI

python AutoTranscriptGUI.py

🔍 Whisper Model Comparison Summary

Model	VRAM (Min)	⚙️ Performance	🎯 Use Case	🌐 Translate into English
tiny	≥ 1 GB	⚡ Very Fast	Quick tests, low-resource devices	✅
base	≥ 2 GB	⚡ Fast	Simple transcriptions, short audio	✅
small	≥ 4 GB	⚖️ Balanced	Decent accuracy and speed for general use	✅
medium	≥ 8 GB	🕒 Slower	High-quality results for longer files	✅
large-v1	≥ 10 GB	🐢 Slower	Older but still strong performer	✅
large-v2	≥ 10 GB	🐢 Slower	More robust, especially with noisy inputs	✅
large-v3	≥ 12 GB	🐌 Slowest	Highest accuracy offline, latest version	✅
large-v3-turbo	≥ 8–10 GB	⚡ Fastest	High-speed, high-accuracy, great multilingual support	❌

🧠 Recommendation

After testing the large-v3-turbo model more than 10 times, I can confidently say it is the fastest and most accurate among all Whisper models included in this app.

🖥️ My system has 4GB of VRAM, and despite being under the recommended VRAM for large models, large-v3-turbo still performed exceptionally well.

⚠️ Note: Your experience may vary depending on your GPU and available VRAM. Use this recommendation as a reference, not a guarantee. If you encounter performance issues, try smaller models like medium or small.

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🖥️ CLI Mode (Optional)

You can still use the command-line version via autosub.py:

python autosub.py myvideo.mp4 -l ja --translate --model base

CLI Options

Option	Description
filename	File path
-l, --language	Force language (e.g. en, es, zh)
-t, --translate	Translate to English
-o, --openai	Use OpenAI API
--model	Whisper model to use
--debug	Enable debug mode
--keep	Keep intermediate WAV file

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📝 Output

• Subtitles are saved as .srt files in the same folder as your media.
• If translated, original and translated text will be preserved.

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🧪 Example GUI Workflow

1. Open GUI
2. Select video/audio file
3. Choose language and Whisper model
4. (Optional) Enable "Translate to English"
5. Click Start Transcription

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🙏 Credits

• Built with OpenAI Whisper
• Powered by Faster-Whisper
• GUI built with CustomTkinter
• Thank you General Koi, for the great help in testing and reviewing the Japanese transcripts.

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📄 License

MIT License — free for personal and commercial use.