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| title: Polyglot Translation Backend | |
| emoji: π | |
| colorFrom: blue | |
| colorTo: green | |
| sdk: docker | |
| pinned: false | |
| license: mit | |
| app_port: 7860 | |
| # Polyglot Translation Backend - Quantized Models | |
| Real-time speech transcription and translation API with Socket.IO for WebSocket communication. This version uses INT8 quantized models for improved performance and reduced memory footprint. | |
| ## Features | |
| - **Real-time Speech Recognition**: Support for English, Swahili, Kikuyu, Kamba, Kimeru, Luo, and Somali | |
| - **Translation**: Multi-language translation using NLLB models | |
| - **Text-to-Speech**: Generate speech in multiple languages | |
| - **WebSocket Support**: Real-time communication via Socket.IO | |
| - **Model Quantization**: INT8 dynamic quantization for faster inference | |
| ## API Endpoints | |
| - `GET /health` - Health check endpoint | |
| - `WebSocket /` - Socket.IO connection for real-time communication | |
| ## Environment | |
| This Space requires a HuggingFace token for model access. The token is automatically provided by HuggingFace Spaces when configured as a secret. | |
| ## Technical Details | |
| - **Framework**: FastAPI with Socket.IO | |
| - **Models**: | |
| - ASR: Whisper (English) and Wav2Vec2-BERT (African languages) | |
| - Translation: NLLB-600M fine-tuned model | |
| - TTS: VITS models for each language | |
| - **Optimization**: INT8 dynamic quantization via PyTorch | |