How Tiny Can Analog Filterbank Features Be Made for Ultra-low-power On-device Keyword Spotting?
Analog feature extraction is a power-efficient and re-emerging signal processing paradigm for implementing the front-end feature extractor in on device keyword-spotting systems. Despite its power efficiency and re-emergence, there is little consensus on what values the architectural parameters of its critical block, the analog filterbank, should be set to, even though they strongly influence power consumption. Towards building consensus and approaching fundamental power consumption limits, we find via simulation that through careful selection of its architectural parameters, the power of a typical state-of-the-art analog filterbank could be reduced by 33.6x, while sacrificing only 1.8% in downstream 10-word keyword spotting accuracy through a back-end neural network.
Code (0)
등록된 구현이 없습니다.
Tasks
Keyword SpottingSimilar Papers 제목 키워드 기반
VAD to the Bone: Ultra-Tiny Speech Activity Detection for Edge Deployment
Voice activity detection (VAD) triggers downstream speech processing in always-on systems under strict memory, latency, and compute constraints. Recent compact models report strong accuracy but rely on components that ar…
Activity DetectionFilterbank design for end-to-end speech separation
Single-channel speech separation has recently made great progress thanks to learned filterbanks as used in ConvTasNet. In parallel, parameterized filterbanks have been proposed for speaker recognition where only center f…
Speaker RecognitionSpeech SeparationA Universal Learnable Audio Frontend
Mel-filterbanks are fixed, engineered audio features which emulate human perception and have lived through the history of audio understanding up to today. However, their undeniable qualities are counterbalanced by the fu…
Audio ClassificationLEAF: A Learnable Frontend for Audio Classification
Mel-filterbanks are fixed, engineered audio features which emulate human perception and have been used through the history of audio understanding up to today. However, their undeniable qualities are counterbalanced by th…
Audio ClassificationClassificationGeneral ClassificationFlexible and Fully Quantized Ultra-Lightweight TinyissimoYOLO for Ultra-Low-Power Edge Systems
This paper deploys and explores variants of TinyissimoYOLO, a highly flexible and fully quantized ultra-lightweight object detection network designed for edge systems with a power envelope of a few milliwatts. With exper…
object-detectionObject Detection