Industry Expert Blogs
How to Achieve High-Accuracy Keyword Spotting on Cortex-M Processorsarm Blogs - Vikas ChandraJan. 24, 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
- IoT and Ethernet: Enabling Seamless Connectivity and Smart Solutions
- Adding RISC-V CPU Custom Extensions Can Boost Performance, Reduce Power, and Cut Cost in 5G, AI. AR/VR, and IoT applications