A 23μW Solar-Powered Keyword-Spotting ASIC with Ring-Oscillator-Based Time-Domain Feature Extraction
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Date
2022
Publication Type
Conference Paper
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yes
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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 0.2μW-to-1 μW 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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published
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Book title
2022 IEEE International Solid- State Circuits Conference (ISSCC)
Volume
65
Pages / Article No.
370 - 372
Publisher
IEEE
Event
69th International Solid-State Circuits Conference (ISSCC 2022)
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Software
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08836 - Delbrück, Tobias (Tit.-Prof.)
02533 - Institut für Neuroinformatik / Institute of Neuroinformatics