Voice Activity Detection with >83 Accuracy under SNR down to −3dB at 1.19μ W and 0.07mm2 in 40nm

摘要

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). $1.19-mumathrm{W}$ power and 0.07mm^{2 area are shown in 40nm.}