mlsanityData to 7 Oct 2026

End-to-End Streaming Keyword Spotting

arXiv 1812.02802 ↗First posted 6 Dec 2018cs.CLcited by 25

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Abstract (arXiv)

We present a system for keyword spotting that, except for a frontend component for feature generation, it is entirely contained in a deep neural network (DNN) model trained "end-to-end" to predict the presence of the keyword in a stream of audio. The main contributions of this work are, first, an efficient memoized neural network topology that aims at making better use of the parameters and associated computations in the DNN by holding a memory of previous activations distributed over the depth of the DNN. The second contribution is a method to train the DNN, end-to-end, to produce the keyword spotting score. This system significantly outperforms previous approaches both in terms of quality of detection as well as size and computation.

Key facts. Cited by 25 papers in the map (data through 7 Oct 2026). First posted on arXiv 6 Dec 2018.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 5; 2022: 6; 2023: 5; 2024: 7; 2025: 1; 2026: 1.

25 papers.

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  1. 2021Deep Spoken Keyword Spotting: An Overviewcited by 43
  2. 2021Noisy student-teacher training for robust keyword spottingcited by 10
  3. 2022Production federated keyword spotting via distillation, filtering, and joint federated-centralized trainingcited by 9
  4. 2021Personalized Keyphrase Detection using Speaker and Environment Informationcited by 8
  5. 2022Tiny, always-on and fragile: Bias propagation through design choices in on-device machine learning workflowscited by 8
  6. 2024Self-Learning for Personalized Keyword Spotting on Ultra-Low-Power Audio Sensorscited by 7
  7. 2021End-to-End Open Vocabulary Keyword Searchcited by 6
  8. 2023PhantomSound: Black-Box, Query-Efficient Audio Adversarial Attack via Split-Second Phoneme Injectioncited by 5
  9. 2022LiCo-Net: Linearized Convolution Network for Hardware-efficient Keyword Spottingcited by 4
  10. 2023Sharing Low Rank Conformer Weights for Tiny Always-On Ambient Speech Recognition Modelscited by 4
  11. 2024Utilizing TTS Synthesized Data for Efficient Development of Keyword Spotting Modelcited by 4
  12. 2022HEiMDaL: Highly Efficient Method for Detection and Localization of wake-wordscited by 3
13 more
  1. 2023Locale Encoding For Scalable Multilingual Keyword Spotting Modelscited by 3
  2. 2022Exploring Sequence-to-Sequence Transformer-Transducer Models for Keyword Spottingcited by 2
  3. 2024Synth4Kws: Synthesized Speech for User Defined Keyword Spotting in Low Resource Environmentscited by 2
  4. 2024GE2E-KWS: Generalized End-to-End Training and Evaluation for Zero-shot Keyword Spottingcited by 2
  5. 2021Multi-task Learning with Cross Attention for Keyword Spottingcited by 1
  6. 2022I see what you hear: a vision-inspired method to localize wordscited by 1
  7. 2023Personalizing Keyword Spotting with Speaker Informationcited by 1
  8. 2024Adversarial training of Keyword Spotting to Minimize TTS Data Overfittingcited by 1
  9. 2023Handling the Alignment for Wake Word Detection: A Comparison Between Alignment-Based, Alignment-Free and Hybrid Approachescited by 0
  10. 2024High-precision Voice Search Query Correction via Retrievable Speech-text Embedingscited by 0
  11. 2024RepCNN: Micro-sized, Mighty Models for Wakeword Detectioncited by 0
  12. 2025GraphemeAug: A Systematic Approach to Synthesized Hard Negative Keyword Spotting Examplescited by 0
  13. 2026Training Intelligent Voice Assistant Wakeup with Controllable Synthetic Conversationscited by 0