Voice Activity Detection with >83% Accuracy under SNR down to −3dB at $1.19\mu \mathrm{W}$ and 0.07mm2 in 40nm

This work presents a voice activity detector for keyword spotting in self-powered speech interfaces with sub-syllable latency. A simple decision stump classifier and time averaging are introduced to provide >83% accuracy in noisy environments with SNR down to −3dB for reliable operation under a wide range of usage contexts (8–15dB lower than prior art).
$1.19-\mu\mathrm{W}$
power and 0.07mm
²
area are shown in 40nm.