mlsanityData to 7 Oct 2026

Self-Supervised Models for Phoneme Recognition: Applications in Children's Speech for Reading Learning

arXiv 2503.04710 ↗First posted 6 Mar 2025cs.SD cs.AI eess.AScited by 6

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Abstract (arXiv)

Child speech recognition is still an underdeveloped area of research due to the lack of data (especially on non-English languages) and the specific difficulties of this task. Having explored various architectures for child speech recognition in previous work, in this article we tackle recent self-supervised models. We first compare wav2vec 2.0, HuBERT and WavLM models adapted to phoneme recognition in French child speech, and continue our experiments with the best of them, WavLM base+. We then further adapt it by unfreezing its transformer blocks during fine-tuning on child speech, which greatly improves its performance and makes it significantly outperform our base model, a Transformer+CTC. Finally, we study in detail the behaviour of these two models under the real conditions of our application, and show that WavLM base+ is more robust to various reading tasks and noise levels. Index Terms: speech recognition, child speech, self-supervised learning

Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). Builds on 17 of its 32 references that are in the map. First posted on arXiv 6 Mar 2025.

Builds on

17 of 32 references.

References · 17

  1. 2017Attention Is All You Needcited by 59,932
  2. 2020wav2vec 2.0: A Framework for Self-Supervised Learning of Speech Representationscited by 3,853
  3. 2021HuBERT: Self-Supervised Speech Representation Learning by Masked Prediction of Hidden Unitscited by 2,301
  4. 2021WavLM: Large-Scale Self-Supervised Pre-Training for Full Stack Speech Processingcited by 1,609
  5. 2015Listen, Attend and Spellcited by 542
  6. 2019Libri-Light: A Benchmark for ASR with Limited or No Supervisioncited by 462
  7. 2021VoxPopuli: A Large-Scale Multilingual Speech Corpus for Representation Learning, Semi-Supervised Learning and Interpretationcited by 455
  8. 2021GigaSpeech: An Evolving, Multi-domain ASR Corpus with 10,000 Hours of Transcribed Audiocited by 391
  9. 2022Self-Supervised Speech Representation Learning: A Reviewcited by 258
  10. 2019A Comparative Study on Transformer vs RNN in Speech Applicationscited by 210
  11. 2023My Science Tutor (MyST) -- A Large Corpus of Children's Conversational Speechcited by 26
  12. 2023Towards Better Domain Adaptation for Self-supervised Models: A Case Study of Child ASRcited by 23
5 more
  1. 2018Transfer Learning from Adult to Children for Speech Recognition: Evaluation, Analysis and Recommendationscited by 21
  2. 2021End-to-End Neural Systems for Automatic Children Speech Recognition: An Empirical Studycited by 17
  3. 2022A Wav2vec2-Based Experimental Study on Self-Supervised Learning Methods to Improve Child Speech Recognitioncited by 15
  4. 2024Analysis of Self-Supervised Speech Models on Children's Speech and Infant Vocalizationscited by 7
  5. 2021End-to-end acoustic modelling for phone recognition of young readerscited by 3

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 2; 2026: 4.

6 papers.

  1. 2025BabyHuBERT: Multilingual Self-Supervised Learning for Segmenting Speakers in Child-Centered Long-Form Recordingscited by 5
  2. 2026Mind the Shift: Using Delta SSL Embeddings to Enhance Child ASRcited by 3
  3. 2025Enhancing GOP in CTC-Based Mispronunciation Detection with Phonological Knowledgecited by 2
  4. 2026Edge Phoneme Recognition for Children's Speech through Age-Aware Trainingcited by 0
  5. 2026Deep Learning Techniques for Phoneme Recognition in Italian Children' s Speechcited by 0
  6. 2026Child-Adapted Structured Phonological Representations for Interpretable Speech Sound Analysiscited by 0