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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.

read1 min views1 publishedJun 20, 2026

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What I Built

Omni-VRAM is an open-source voice AI platform with 28 modules.

GitHub: https://github.com/Liangchenxu/Omni-VRAM

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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

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Tech Stack

Python, PyTorch, CUDA, FastAPI, Whisper

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Installation

source & further reading
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