mlsanityData to 14 Oct 2026

Query-by-Example Search with Discriminative Neural Acoustic Word Embeddings

arXiv 1706.03818 ↗First posted 12 Jun 2017cs.CLcited by 22

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Abstract (arXiv)

Query-by-example search often uses dynamic time warping (DTW) for comparing queries and proposed matching segments. Recent work has shown that comparing speech segments by representing them as fixed-dimensional vectors --- acoustic word embeddings --- and measuring their vector distance (e.g., cosine distance) can discriminate between words more accurately than DTW-based approaches. We consider an approach to query-by-example search that embeds both the query and database segments according to a neural model, followed by nearest-neighbor search to find the matching segments. Earlier work on embedding-based query-by-example, using template-based acoustic word embeddings, achieved competitive performance. We find that our embeddings, based on recurrent neural networks trained to optimize word discrimination, achieve substantial improvements in performance and run-time efficiency over the previous approaches.

Key facts. Cited by 22 papers in the map (data through 14 Oct 2026). First posted on arXiv 12 Jun 2017.

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Citing papers per year: 2021: 6; 2022: 6; 2023: 4; 2024: 2; 2025: 2; 2026: 2.

22 papers.

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  1. 2022Self-Supervised Speech Representation Learning: A Reviewcited by 260
  2. 2022Analyzing Acoustic Word Embeddings from Pre-trained Self-supervised Speech Modelscited by 21
  3. 2023Matching Latent Encoding for Audio-Text based Keyword Spottingcited by 15
  4. 2021Attention-Based Keyword Localisation in Speech using Visual Groundingcited by 13
  5. 2021Do Acoustic Word Embeddings Capture Phonological Similarity? An Empirical Studycited by 8
  6. 2021Multilingual transfer of acoustic word embeddings improves when training on languages related to the target zero-resource languagecited by 7
  7. 2022Keyword localisation in untranscribed speech using visually grounded speech modelscited by 7
  8. 2021CNN-based Spoken Term Detection and Localization without Dynamic Programmingcited by 6
  9. 2023Towards hate speech detection in low-resource languages: Comparing ASR to acoustic word embeddings on Wolof and Swahilicited by 5
  10. 2024Improving Acoustic Word Embeddings through Correspondence Training of Self-supervised Speech Representationscited by 3
  11. 2022Integrating Form and Meaning: A Multi-Task Learning Model for Acoustic Word Embeddingscited by 2
  12. 2022Bootstrapping meaning through listening: Unsupervised learning of spoken sentence embeddingscited by 2
10 more
  1. 2023Acoustic Word Embeddings for Untranscribed Target Languages with Continued Pretraining and Learned Poolingcited by 2
  2. 2023Leveraging multilingual transfer for unsupervised semantic acoustic word embeddingscited by 2
  3. 2022Learning Phone Recognition from Unpaired Audio and Phone Sequences Based on Generative Adversarial Networkcited by 1
  4. 2021Spoken Term Detection Methods for Sparse Transcription in Very Low-resource Settingscited by 0
  5. 2021BBS-KWS:The Mandarin Keyword Spotting System Won the Video Keyword Wakeup Challengecited by 0
  6. 2024Cross-Lingual Query-by-Example Spoken Term Detection: A Transformer-Based Approachcited by 0
  7. 2025Noise-Agnostic Multitask Whisper Training for Reducing False Alarm Errors in Call-for-Help Detectioncited by 0
  8. 2025Joint Multimodal Contrastive Learning for Robust Spoken Term Detection and Keyword Spottingcited by 0
  9. 2026PCOV-KWS: Multi-task Learning for Personalized Customizable Open Vocabulary Keyword Spottingcited by 0
  10. 2026ProKWS: Personalized Keyword Spotting via Collaborative Learning of Phonemes and Prosodycited by 0