English
Industry Expert Blogs
|
How to Achieve High-Accuracy Keyword Spotting on Cortex-M Processorsarm Blogs - Vikas Chandran, ArmJan. 19, 2018 |
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.
Related Blogs
- How to Achieve High-Accuracy Keyword Spotting on Cortex-M Processors
- Ecosystem Collaboration Drives New AMBA Specification for Chiplets
- Mitigating Side-Channel Attacks In Post Quantum Cryptography (PQC) With Secure-IC Solutions
- ARM vs RISC-V: Beginning of a new era
- Arm and Arteris Drive Innovation in Automotive SoCs