mlsanityData to 7 Oct 2026

Deep Spoken Keyword Spotting: An Overview

arXiv 2111.10592 ↗First posted 20 Nov 2021cs.SD cs.HC cs.LGcited by 43

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Abstract (arXiv)

Spoken keyword spotting (KWS) deals with the identification of keywords in audio streams and has become a fast-growing technology thanks to the paradigm shift introduced by deep learning a few years ago. This has allowed the rapid embedding of deep KWS in a myriad of small electronic devices with different purposes like the activation of voice assistants. Prospects suggest a sustained growth in terms of social use of this technology. Thus, it is not surprising that deep KWS has become a hot research topic among speech scientists, who constantly look for KWS performance improvement and computational complexity reduction. This context motivates this paper, in which we conduct a literature review into deep spoken KWS to assist practitioners and researchers who are interested in this technology. Specifically, this overview has a comprehensive nature by covering a thorough analysis of deep KWS systems (which includes speech features, acoustic modeling and posterior handling), robustness methods, applications, datasets, evaluation metrics, performance of deep KWS systems and audio-visual KWS. The analysis performed in this paper allows us to identify a number of directions for future research, including directions adopted from automatic speech recognition research and directions that are unique to the problem of spoken KWS.

Key facts. Cited by 43 papers in the map (data through 7 Oct 2026). Builds on 86 of its 269 references that are in the map. First posted on arXiv 20 Nov 2021.

Builds on

86 of 269 references.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 9; 2023: 11; 2024: 9; 2025: 8; 2026: 6.

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  1. 2024On-Device Domain Learning for Keyword Spotting on Low-Power Extreme Edge Embedded Systemscited by 13
  2. 2023Few-Shot Open-Set Learning for On-Device Customization of KeyWord Spotting Systemscited by 9
  3. 2023Online Continual Learning in Keyword Spotting for Low-Resource Devices via Pooling High-Order Temporal Statisticscited by 9
  4. 2022Rainbow Keywords: Efficient Incremental Learning for Online Spoken Keyword Spottingcited by 8
  5. 2023Open-vocabulary Keyword-spotting with Adaptive Instance Normalizationcited by 8
  6. 2024Self-Learning for Personalized Keyword Spotting on Ultra-Low-Power Audio Sensorscited by 7
  7. 2022VSVC: Backdoor attack against Keyword Spotting based on Voiceprint Selection and Voice Conversioncited by 6
  8. 2022Keyword Spotting System and Evaluation of Pruning and Quantization Methods on Low-power Edge Microcontrollerscited by 4
  9. 2022LiCo-Net: Linearized Convolution Network for Hardware-efficient Keyword Spottingcited by 4
  10. 2024Noise-Robust Keyword Spotting through Self-supervised Pretrainingcited by 4
  11. 2024MM-KWS: Multi-modal Prompts for Multilingual User-defined Keyword Spottingcited by 4
  12. 2025AnalyticKWS: Towards Exemplar-Free Analytic Class Incremental Learning for Small-footprint Keyword Spottingcited by 4
31 more
  1. 2022Improving Label-Deficient Keyword Spotting Through Self-Supervised Pretrainingcited by 3
  2. 2022Filterbank Learning for Noise-Robust Small-Footprint Keyword Spottingcited by 3
  3. 2023Speech Understanding on Tiny Devices with A Learning Cachecited by 3
  4. 2024ED-sKWS: Early-Decision Spiking Neural Networks for Rapid,and Energy-Efficient Keyword Spottingcited by 3
  5. 2025End-to-End Efficiency in Keyword Spotting: A System-Level Approach for Embedded Microcontrollerscited by 3
  6. 2022Exploring Sequence-to-Sequence Transformer-Transducer Models for Keyword Spottingcited by 2
  7. 2023To Wake-up or Not to Wake-up: Reducing Keyword False Alarm by Successive Refinementcited by 2
  8. 2023Latent Phrase Matching for Dysarthric Speechcited by 2
  9. 2024GE2E-KWS: Generalized End-to-End Training and Evaluation for Zero-shot Keyword Spottingcited by 2
  10. 2025OASI: Objective-Aware Surrogate Initialization for Multi-Objective Bayesian Optimization in TinyML Keyword Spottingcited by 2
  11. 2026Hardware-accelerated graph neural networks: an alternative approach for neuromorphic event-based audio classification and keyword spotting on SoC FPGAcited by 2
  12. 2023Spot keywords from very noisy and mixed speechcited by 1
  13. 2023Robust Wake-Up Word Detection by Two-stage Multi-resolution Ensemblescited by 1
  14. 2023Personalizing Keyword Spotting with Speaker Informationcited by 1
  15. 2024End-to-End User-Defined Keyword Spotting using Shifted Delta Coefficientscited by 1
  16. 2024Text-Based Detection of On-Hold Scripts in Contact Center Callscited by 1
  17. 2025LHGNN: Local-Higher Order Graph Neural Networks For Audio Classification and Taggingcited by 1
  18. 2025Adaptive Noise Resilient Keyword Spotting Using One-Shot Learningcited by 1
  19. 2022AB/BA analysis: A framework for estimating keyword spotting recall improvement while maintaining audio privacycited by 0
  20. 2022Harnessing the Power of Explanations for Incremental Training: A LIME-Based Approachcited by 0
  21. 2023Handling the Alignment for Wake Word Detection: A Comparison Between Alignment-Based, Alignment-Free and Hybrid Approachescited by 0
  22. 2023Semi-Supervised Federated Learning for Keyword Spottingcited by 0
  23. 2024Advancing Airport Tower Command Recognition: Integrating Squeeze-and-Excitation and Broadcasted Residual Learningcited by 0
  24. 2025Keyword Spotting with Hyper-Matched Filters for Small Footprint Devicescited by 0
  25. 2025Keyword Mamba: Spoken Keyword Spotting with State Space Modelscited by 0
  26. 2025Zero-Shot KWS for Children's Speech using Layer-Wise Features from SSL Modelscited by 0
  27. 2026OnDA: On-device Channel Pruning for Efficient Personalized Keyword Spottingcited by 0
  28. 2026"OK Aura, Be Fair With Me": Demographics-Agnostic Training for Bias Mitigation in Wake-up Word Detectioncited by 0
  29. 2026Keyword spotting using convolutional neural network for speech recognition in Hindicited by 0
  30. 2026Does language matter for spoken word classification? A multilingual generative meta-learning approachcited by 0
  31. 2026A Neuromorphic Trigger for Efficient Audio Event Detectioncited by 0