<![CDATA[IEEKER Embedded Blog]]>https://ieeker-embedded.hashnode.devRSS for NodeWed, 28 Oct 2026 22:50:07 GMT60<![CDATA[Local Speech Recognition and TTS on RK3588 NPU for Industrial IoT]]>https://ieeker-embedded.hashnode.dev/local-speech-recognition-and-tts-on-rk3588-npu-for-industrial-iothttps://ieeker-embedded.hashnode.dev/local-speech-recognition-and-tts-on-rk3588-npu-for-industrial-iotTue, 27 Oct 2026 03:47:54 GMTEdge AI on embedded hardware continues to grow for privacy-sensitive industrial applications. The RK3588’s integrated NPU offers strong performance for running speech models locally, without relying on cloud servers.

This tutorial walks through setting up local ASR and TTS workloads on the RK3588 SBC, building a fully offline voice control solution.

Required Hardware

  • RK3588 single-board computer
  • Stable 5V power supply
  • Microphone and speaker modules
  • Heatsink for temperature control

Implementation Steps

  1. Flash the official embedded Linux firmware
  2. Prepare RKNN model packages for speech AI
  3. Configure audio capture and output pipeline
  4. Test end-to-end speech-to-text and text-to-speech inference

All AI inference runs on-board. This eliminates network latency and keeps audio data local, which is ideal for factory equipment, on-site controllers, and isolated IoT devices.

Final Notes

For engineers developing offline voice products, the RK3588 is a solid option thanks to mature Linux support and optimized NPU tools.

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