Industry Expert Blogs

It IS possible to optimize neural network architectures to fit within the memory and compute constraints of microcontrollers – without sacrificing accuracy. We explain how, and explore the potential of depthwise separable convolutional neural networks for implementing keyword spotting on Cortex-M processors.

Keyword spotting (KWS) is a critical component for enabling speech-based user interactions on smart devices. It requires real-time response and high accuracy to ensure a good user experience. Recently, neural networks have become an attractive choice for KWS architecture because of their superior accuracy compared to traditional speech-processing algorithms.

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