Adolfo Delorenzo
dc3e67e17b
Features: - Speaker management system with unique IDs and colors - Visual speaker selection with avatars and color coding - Automatic language detection per speaker - Real-time translation for all speakers' languages - Conversation history with speaker attribution - Export conversation as text file - Persistent speaker data in localStorage UI Components: - Speaker toolbar with add/remove controls - Active speaker indicators - Conversation view with color-coded messages - Settings toggle for multi-speaker mode - Mobile-responsive speaker buttons Technical Implementation: - SpeakerManager class handles all speaker operations - Automatic translation to all active languages - Conversation entries with timestamps - Translation caching per language - Clean separation of original vs translated text - Support for up to 8 concurrent speakers User Experience: - Click to switch active speaker - Visual feedback for active speaker - Conversation flows naturally with colors - Export feature for meeting minutes - Clear conversation history option - Seamless single/multi speaker mode switching This enables group conversations where each participant can speak in their native language and see translations in real-time. 🤖 Generated with [Claude Code](https://claude.ai/code) Co-Authored-By: Claude <noreply@anthropic.com> |
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|---|---|---|
| static | ||
| templates | ||
| venv | ||
| .gitignore | ||
| app.py | ||
| GPU_SUPPORT.md | ||
| health-monitor.py | ||
| maintenance.sh | ||
| package-lock.json | ||
| package.json | ||
| README_TYPESCRIPT.md | ||
| README.md | ||
| requirements.txt | ||
| setup-script.sh | ||
| tsconfig.json | ||
| tts_test_output.mp3 | ||
| tts-debug-script.py | ||
| validators.py | ||
| whisper_config.py | ||
Voice Language Translator
A mobile-friendly web application that translates spoken language between multiple languages using:
- Gemma 3 open-source LLM via Ollama for translation
- OpenAI Whisper for speech-to-text
- OpenAI Edge TTS for text-to-speech
Supported Languages
- Arabic
- Armenian
- Azerbaijani
- English
- French
- Georgian
- Kazakh
- Mandarin
- Farsi
- Portuguese
- Russian
- Spanish
- Turkish
- Uzbek
Setup Instructions
-
Install the required Python packages:
pip install -r requirements.txt -
Make sure you have Ollama installed and the Gemma 3 model loaded:
ollama pull gemma3 -
Ensure your OpenAI Edge TTS server is running on port 5050.
-
Run the application:
python app.py -
Open your browser and navigate to:
http://localhost:8000
Usage
- Select your source language from the dropdown menu
- Press the microphone button and speak
- Press the button again to stop recording
- Wait for the transcription to complete
- Select your target language
- Press the "Translate" button
- Use the play buttons to hear the original or translated text
Technical Details
- The app uses Flask for the web server
- Audio is processed client-side using the MediaRecorder API
- Whisper for speech recognition with language hints
- Ollama provides access to the Gemma 3 model for translation
- OpenAI Edge TTS delivers natural-sounding speech output
Mobile Support
The interface is fully responsive and designed to work well on mobile devices.