Implementing Keyword Spotting on the MCUX947 Microcontroller with Integrated NPU
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arXiv
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| Main Authors: | , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866912441309331456 |
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| author | Jakuš, Petar Džapo, Hrvoje |
| author_facet | Jakuš, Petar Džapo, Hrvoje |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2506_08911 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Implementing Keyword Spotting on the MCUX947 Microcontroller with Integrated NPU Jakuš, Petar Džapo, Hrvoje Human-Computer Interaction Hardware Architecture Machine Learning Performance Sound 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. |
| title | Implementing Keyword Spotting on the MCUX947 Microcontroller with Integrated NPU |
| topic | Human-Computer Interaction Hardware Architecture Machine Learning Performance Sound |
| url | https://arxiv.org/abs/2506.08911 |