mlsanityData to 14 Oct 2026

Few-Shot Keyword Spotting With Prototypical Networks

arXiv 2007.14463 ↗First posted 25 Jul 2020eess.AS cs.LG cs.SDcited by 18

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Abstract (arXiv)

Recognizing a particular command or a keyword, keyword spotting has been widely used in many voice interfaces such as Amazon's Alexa and Google Home. In order to recognize a set of keywords, most of the recent deep learning based approaches use a neural network trained with a large number of samples to identify certain pre-defined keywords. This restricts the system from recognizing new, user-defined keywords. Therefore, we first formulate this problem as a few-shot keyword spotting and approach it using metric learning. To enable this research, we also synthesize and publish a Few-shot Google Speech Commands dataset. We then propose a solution to the few-shot keyword spotting problem using temporal and dilated convolutions on prototypical networks. Our comparative experimental results demonstrate keyword spotting of new keywords using just a small number of samples.

Key facts. Cited by 18 papers in the map (data through 14 Oct 2026). First posted on arXiv 25 Jul 2020.

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2021: 2; 2022: 5; 2023: 3; 2024: 3; 2025: 1; 2026: 4.

18 papers.

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  1. 2022Learning from Few Examples: A Summary of Approaches to Few-Shot Learningcited by 86
  2. 2022Meta Learning for Natural Language Processing: A Surveycited by 26
  3. 2021Teaching keyword spotters to spot new keywords with limited examplescited by 9
  4. 2023Few-Shot Open-Set Learning for On-Device Customization of KeyWord Spotting Systemscited by 9
  5. 2022Dummy Prototypical Networks for Few-Shot Open-Set Keyword Spottingcited by 7
  6. 2024Self-Learning for Personalized Keyword Spotting on Ultra-Low-Power Audio Sensorscited by 7
  7. 2022On the Efficiency of Integrating Self-supervised Learning and Meta-learning for User-defined Few-shot Keyword Spottingcited by 5
  8. 2021Auto-KWS 2021 Challenge: Task, Datasets, and Baselinescited by 2
  9. 2023Federated Few-shot Learning for Cough Classification with Edge Devicescited by 1
  10. 2025Enhancing Few-shot Keyword Spotting Performance through Pre-Trained Self-supervised Speech Modelscited by 1
  11. 2022Privacy Enhancement for Cloud-Based Few-Shot Learningcited by 0
  12. 2023Improving Small Footprint Few-shot Keyword Spotting with Supervision on Auxiliary Datacited by 0
6 more
  1. 2024Multitaper mel-spectrograms for keyword spottingcited by 0
  2. 2024Visually Grounded Speech Models for Low-resource Languages and Cognitive Modellingcited by 0
  3. 2026OnDA: On-device Channel Pruning for Efficient Personalized Keyword Spottingcited by 0
  4. 2026Scaling few-shot spoken word classification with generative meta-continual learningcited by 0
  5. 2026Training Intelligent Voice Assistant Wakeup with Controllable Synthetic Conversationscited by 0
  6. 2026Towards Model as a Library: Offline, Community-Sourced AI for Low-Resource African Languagescited by 0