mlsanityData to 7 Oct 2026

Small-Footprint Keyword Spotting on Raw Audio Data with Sinc-Convolutions

arXiv 1911.02086 ↗First posted 5 Nov 2019eess.AS cs.CL cs.SDcited by 20

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Abstract (arXiv)

Keyword Spotting (KWS) enables speech-based user interaction on smart devices. Always-on and battery-powered application scenarios for smart devices put constraints on hardware resources and power consumption, while also demanding high accuracy as well as real-time capability. Previous architectures first extracted acoustic features and then applied a neural network to classify keyword probabilities, optimizing towards memory footprint and execution time. Compared to previous publications, we took additional steps to reduce power and memory consumption without reducing classification accuracy. Power-consuming audio preprocessing and data transfer steps are eliminated by directly classifying from raw audio. For this, our end-to-end architecture extracts spectral features using parametrized Sinc-convolutions. Its memory footprint is further reduced by grouping depthwise separable convolutions. Our network achieves the competitive accuracy of 96.4% on Google's Speech Commands test set with only 62k parameters.

Key facts. Cited by 20 papers in the map (data through 7 Oct 2026). First posted on arXiv 5 Nov 2019.

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Citing papers per year: 2021: 7; 2022: 6; 2023: 2; 2024: 1; 2025: 3; 2026: 1.

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  1. 2021Deep Spoken Keyword Spotting: An Overviewcited by 43
  2. 2021How to Design a Three-Stage Architecture for Audio-Visual Active Speaker Detection in the Wildcited by 30
  3. 2021A Streaming End-to-End Framework For Spoken Language Understandingcited by 8
  4. 2022Personalized Keyword Spotting through Multi-task Learningcited by 7
  5. 2021Ultra-Low Power Keyword Spotting at the Edgecited by 6
  6. 2024Boosting keyword spotting through on-device learnable user speech characteristicscited by 4
  7. 2022Filterbank Learning for Noise-Robust Small-Footprint Keyword Spottingcited by 3
  8. 2023Speech Understanding on Tiny Devices with A Learning Cachecited by 3
  9. 2025End-to-End Efficiency in Keyword Spotting: A System-Level Approach for Embedded Microcontrollerscited by 3
  10. 2021End-to-end Keyword Spotting using Neural Architecture Search and Quantizationcited by 2
  11. 2021Encoder-Decoder Neural Architecture Optimization for Keyword Spottingcited by 2
  12. 2022Sub 8-Bit Quantization of Streaming Keyword Spotting Models for Embedded Chipsetscited by 2
8 more
  1. 2023To Wake-up or Not to Wake-up: Reducing Keyword False Alarm by Successive Refinementcited by 2
  2. 2021Behavior of Keyword Spotting Networks Under Noisy Conditionscited by 0
  3. 2022A Fast Network Exploration Strategy to Profile Low Energy Consumption for Keyword Spottingcited by 0
  4. 2022A Study of Designing Compact Audio-Visual Wake Word Spotting System Based on Iterative Fine-Tuning in Neural Network Pruningcited by 0
  5. 2022A 14uJ/Decision Keyword Spotting Accelerator with In-SRAM-Computing and On Chip Learning for Customizationcited by 0
  6. 2025Keyword Spotting with Hyper-Matched Filters for Small Footprint Devicescited by 0
  7. 2025Keyword Mamba: Spoken Keyword Spotting with State Space Modelscited by 0
  8. 2026SincDPNet: Interpretable Raw-Waveform Bathroom Activity Recognition for Assistive Livingcited by 0