Speech Recognition and TTS in Under 500KB: How It Works on a Microcontroller

Picture this: you’re building a tiny voice assistant for a hardware demo. A phone can handle speech recognition and text-to-speech (TTS) without breaking a sweat, but your microcontroller board has… less than half a megabyte of RAM.

So how can you possibly do speech recognition and speech synthesis in less than 500 KB of memory? The short answer is that you don’t try to run “full speech AI.” You build a very specific pipeline, compress everything aggressively, and obsess over memory reuse.

A great concrete example is Moonshine Micro, an open-source voice stack designed for embedded processors (microcontrollers and DSPs) using a Raspberry Pi RP2350 as a reference platform. Its README describes a complete demo pipeline that can run with about 470 KB of RAM on that class of hardware. (github.com)