@inproceedings{3360eeae92264990a4cba2fd81e4cd9b,
title = "A 23W Solar-Powered Keyword-Spotting ASIC with Ring-Oscillator-Based Time-Domain Feature Extraction",
abstract = "Voice-controlled interfaces on acoustic Internet-of-Things (IoT) sensor nodes and mobile devices require integrated low-power always-on wake-up functions such as Voice Activity Detection (VAD) and Keyword Spotting (KWS) to ensure longer battery life. Most VAD and KWS ICs focused on reducing the power of the feature extractor (FEx) as it is the most power-hungry building block. A serial Fast Fourier Transform (FFT)-based KWS chip [1] achieved 510nW; however, it suffered from a high 64ms latency and was limited to detection of only 1-to-4 keywords (2-to-5 classes). Although the analog FEx [2]-[3] for VAD/KWS reported 0.2W-to-1 W and 10ms-to-100ms latency, neither demonstrated >5 classes in keyword detection. In addition, their voltage-domain implementations cannot benefit from process scaling because the low supply voltage reduces signal swing; and the degradation of intrinsic gain forces transistors to have larger lengths and poor linearity. ",
author = "Kwantae Kim and Chang Gao and Rui Graca and Ilya Kiselev and Yoo, {Hoi Jun} and Tobi Delbruck and Liu, {Shih Chii}",
year = "2022",
doi = "10.1109/ISSCC42614.2022.9731708",
language = "English",
series = "Digest of Technical Papers - IEEE International Solid-State Circuits Conference",
publisher = "Institute of Electrical and Electronics Engineers (IEEE)",
pages = "370--372",
booktitle = "2022 IEEE International Solid-State Circuits Conference, ISSCC 2022",
address = "United States",
note = "2022 IEEE International Solid-State Circuits Conference, ISSCC 2022 ; Conference date: 20-02-2022 Through 26-02-2022",
}