Moonshine Micro — Voice Interfaces for Microcontrollers

Moonshine Voice is an open source AI toolkit for developers building real-time voice agents and applications. Moonshine Micro is a version of that designed specifically for embedded system processors like microcontrollers and DSPs. It includes voice-activity detection, command recognition, and speech synthesis and can run in as little as 500KB RAM.

The memory and compute requirements are designed to fit resource-constrained systems. Figures below are for the RP2350 demo; the detailed memory budget breaks each one down:

Component	Flash	SRAM (arena peak)	Compute
VAD (Voice Activity Detection)	~89 KiB	~36 KiB	~0.8 MMAC/frame (~25 MMAC/second)
STT (SpellingCNN Speech-to-Text)	~1.3 MiB	~346 KiB	~36 MMAC/second
TTS (Klatt synth, waveform synthesis etc.)	~150 KiB	few KiB	~1 MMAC/second
TOTAL (Demo pipeline)	~1.8 MiB	~498 KiB provisioned*	—

Notes:

• Flash is the .text measured with arm-none-eabi-size (model + code + rodata); SRAM is .bss + heap + stacks.
• *The three stages run sequentially and time-share one ~384 KiB TFLM arena, so SRAM is not additive — ~498 KiB is the total RAM provisioned on the 520 KiB RP2350.
• A MAC is one multiply-accumulate; MMAC/s = millions per second during the active (non-idle) stage.

The code is released under the permissive MIT License, usable for commercial applications.

There's a complete end-to-end example showing how to set up a wifi connection on a microcontroller using voice on an RP2350 MCU.

The VAD, STT, and TTS libraries can be used independently of each other, relying on the included TensorFlow Lite Micro library for the neural computations.

Documentation

• Voice Activity Detection
• Speech to Text
• Text to Speech
• Wifi Setup Example

License

This code, apart from the source in third-party/, is licensed under the MIT License — see LICENSE in this directory (also at the repository root).

The SpellingCNN and TinyVadCNN models in models/ are released under the MIT License.

The code in third-party/ is licensed according to the terms of the open source projects it originates from, with details in a LICENSE file in each subfolder.