Building a Voice AI Platform with 28 Modules in Python

A developer built Omni-VRAM, an open-source voice AI platform with 28 modules. The platform includes speech recognition with five Whisper backends, real-time streaming under 200ms latency, speaker diarization, emotion recognition, TTS synthesis, and a meeting assistant with LLM summarization. It supports REST, WebSocket, and gRPC APIs, and runs on Docker with GPU and CPU support.

What I Built Omni-VRAM is an open-source voice AI platform with 28 modules. GitHub: https://github.com/Liangchenxu/Omni-VRAM https://github.com/Liangchenxu/Omni-VRAM Features - Speech Recognition : Whisper with 5 backends faster-whisper, whisper.cpp, ONNX, TensorRT, OpenAI API - Real-time Streaming : <200ms latency - Speaker Diarization : Who spoke when - Emotion Recognition : 6 emotions - TTS Synthesis : Edge-TTS + pyttsx3 - Chinese Processing : Punctuation, tokenization, dialects - Meeting Assistant : Auto summarization with LLM - APIs : REST, WebSocket, gRPC - Docker : GPU and CPU support Tech Stack Python, PyTorch, CUDA, FastAPI, Whisper Installation