This post is Part 1 of 4 in a series covering Voice Activity Detection (VAD) gated Keyword Spotting (KWS) on the ESP32-C3 Lyra, a RISC-V based microcontroller. Precursor work solely focused on KWS on the Lyra can be viewed at Keyword Spotting on ESP32-C3-Lyra V2 Using ESP-IDF.
This is the subject of a project I completed for two of my M.S. courses, Digital Signal Processing and AI-accelerated computing, both taught by Dr. Adly Fam. The goal of this project is to reduce the power consumption of always-on KWS by gating the KWS model behind a lightweight VAD. Rather than running the full KWS model continuously, the VAD listens first — only waking the KWS model when speech is detected.
The VAD: Four-Parameter Approach
The VAD used in this project is based on four acoustic parameters:
- Energy
- Zero Crossing Rate (ZCR)
- The Golay Feature
- The Fast Walsh Hadamard Transform (FWHT)
Power Consumption Results
By running the VAD instead of the full KWS model during silence, the system achieves approximately a 4.8× reduction in average power consumption over time on the ESP32-C3.
This concludes part 1. Continue to part 2 to see how the VAD is structured.
