mlsanityData to 7 Oct 2026

Open-vocabulary Keyword-spotting with Adaptive Instance Normalization

arXiv 2309.08561 ↗First posted 13 Sep 2023eess.AS cs.LG cs.SDcited by 8

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Abstract (arXiv)

Open vocabulary keyword spotting is a crucial and challenging task in automatic speech recognition (ASR) that focuses on detecting user-defined keywords within a spoken utterance. Keyword spotting methods commonly map the audio utterance and keyword into a joint embedding space to obtain some affinity score. In this work, we propose AdaKWS, a novel method for keyword spotting in which a text encoder is trained to output keyword-conditioned normalization parameters. These parameters are used to process the auditory input. We provide an extensive evaluation using challenging and diverse multi-lingual benchmarks and show significant improvements over recent keyword spotting and ASR baselines. Furthermore, we study the effectiveness of our approach on low-resource languages that were unseen during the training. The results demonstrate a substantial performance improvement compared to baseline methods.

Key facts. Cited by 8 papers in the map (data through 7 Oct 2026). Builds on 16 of its 20 references that are in the map. First posted on arXiv 13 Sep 2023.

Builds on

16 of 20 references.

References · 16

  1. 2022Robust Speech Recognition via Large-Scale Weak Supervisioncited by 3,972
  2. 2017Arbitrary Style Transfer in Real-time with Adaptive Instance Normalizationcited by 1,998
  3. 2022FLEURS: Few-shot Learning Evaluation of Universal Representations of Speechcited by 458
  4. 2021VoxPopuli: A Large-Scale Multilingual Speech Corpus for Representation Learning, Semi-Supervised Learning and Interpretationcited by 455
  5. 2021Keyword Transformer: A Self-Attention Model for Keyword Spottingcited by 59
  6. 2021Deep Spoken Keyword Spotting: An Overviewcited by 43
  7. 2020MatchboxNet: 1D Time-Channel Separable Convolutional Neural Network Architecture for Speech Commands Recognitioncited by 36
  8. 2021Query-by-Example Keyword Spotting system using Multi-head Attention and Softtriple Losscited by 25
  9. 2022Learning Audio-Text Agreement for Open-vocabulary Keyword Spottingcited by 20
  10. 2018DONUT: CTC-based Query-by-Example Keyword Spottingcited by 15
  11. 2023Matching Latent Encoding for Audio-Text based Keyword Spottingcited by 15
  12. 2023Flexible Keyword Spotting based on Homogeneous Audio-Text Embeddingcited by 10
4 more
  1. 2022Metric Learning for User-defined Keyword Spottingcited by 7
  2. 2021CNN-based Spoken Term Detection and Localization without Dynamic Programmingcited by 6
  3. 2022Fully Unsupervised Training of Few-shot Keyword Spottingcited by 5
  4. 2023Multilingual Query-by-Example Keyword Spotting with Metric Learning and Phoneme-to-Embedding Mappingcited by 3

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 1; 2024: 5; 2025: 1; 2026: 1.

8 papers.

  1. 2023A Multitask Training Approach to Enhance Whisper with Contextual Biasing and Open-Vocabulary Keyword Spottingcited by 5
  2. 2024Keyword-Guided Adaptation of Automatic Speech Recognitioncited by 5
  3. 2024MM-KWS: Multi-modal Prompts for Multilingual User-defined Keyword Spottingcited by 4
  4. 2024Text-Aware Adapter for Few-Shot Keyword Spottingcited by 2
  5. 2024Text-Based Detection of On-Hold Scripts in Contact Center Callscited by 1
  6. 2024SLiCK: Exploiting Subsequences for Length-Constrained Keyword Spottingcited by 0
  7. 2025Keyword Spotting with Hyper-Matched Filters for Small Footprint Devicescited by 0
  8. 2026ProKWS: Personalized Keyword Spotting via Collaborative Learning of Phonemes and Prosodycited by 0