# Speech Recognition and TTS in Less Than 500 KB

An open-source AI voice toolkit for microcontrollers.

- **Source:** [Hacker News](https://news.ycombinator.com)
- **Published:** 2026-07-14
- **Topic:** [Data & AI](https://brifing.si/c/data-ai)
- **Original article:** <https://github.com/moonshine-ai/moonshine/tree/main/micro>
- **On Brifing:** https://brifing.si/s/1d4d7ce2-7a34-4867-9654-6cb4e5303788

## What is Moonshine Micro?

Moonshine Micro is an open-source AI voice toolkit designed for embedded systems like microcontrollers and DSPs. It can run on low-cost platforms such as the Raspberry Pi RP2350 and uses only 470 KB of RAM.

## Speech Recognition and Text-to-Speech

The toolkit offers features like voice activity detection, command recognition, and neural text-to-speech synthesis. These features can operate efficiently even in resource-constrained systems.

## Memory and Compute Requirements

Moonshine Micro uses only 3.6 MiB Flash and 468 KiB SRAM on the RP2350 demo platform. This ensures the system runs efficiently in low-resource environments.

## TensorFlow Lite Micro Integration

Speech recognition and text-to-speech processes run on the TensorFlow Lite Micro library. This enables neural computations even on microcontrollers.

## MIT License for Usage

Moonshine Micro is released under the MIT License. This facilitates its use in both commercial and open-source projects.

## Future Potential

This technology could enable the widespread adoption of voice-based interfaces in IoT devices and other embedded systems. Low resource requirements offer a broad range of applications.

## Sources covering this story

- https://github.com/moonshine-ai/moonshine/tree/main/micro — 

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_Summary written by Brifing from the original reporting. Copyright in the original article belongs to its publisher; read the full piece at the link above._