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Implementing Keyword Spotting on the MCUX947 Microcontroller with Integrated NPU

Human-Computer Interaction 2025-06-23 v1 Hardware Architecture Machine Learning Performance Sound

Abstract

This paper presents a keyword spotting (KWS) system implemented on the NXP MCXN947 microcontroller with an integrated Neural Processing Unit (NPU), enabling real-time voice interaction on resource-constrained devices. The system combines MFCC feature extraction with a CNN classifier, optimized using Quantization Aware Training to reduce model size with minimal accuracy drop. Experimental results demonstrate a 59x speedup in inference time when leveraging the NPU compared to CPU-only execution, achieving 97.06% accuracy with a model size of 30.58 KB, demonstrating the feasibility of efficient, low-power voice interfaces on embedded platforms.

Keywords

Cite

@article{arxiv.2506.08911,
  title  = {Implementing Keyword Spotting on the MCUX947 Microcontroller with Integrated NPU},
  author = {Petar Jakuš and Hrvoje Džapo},
  journal= {arXiv preprint arXiv:2506.08911},
  year   = {2025}
}

Comments

4 pages

R2 v1 2026-07-01T03:09:20.797Z