A 23W Solar-Powered Keyword-Spotting ASIC with Ring-Oscillator-Based Time-Domain Feature Extraction

Conference Paper (2022)
Author(s)

Kwantae Kim (University of Zürich)

C. Gao (University of Zürich)

Rui Graca (University of Zürich)

Ilya Kiselev (University of Zürich)

Hoi Jun Yoo (Korea Advanced Institute of Science and Technology)

Tobi Delbruck (University of Zürich)

Shih Chii Liu (University of Zürich)

Affiliation
External organisation
DOI related publication
https://doi.org/10.1109/ISSCC42614.2022.9731708
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Publication Year
2022
Language
English
Affiliation
External organisation
Pages (from-to)
370-372
ISBN (electronic)
9781665428002

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.

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