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Child Speech Recognition in Human-Robot Interaction: Problem Solved?

arXiv 2404.17394 ↗First posted 26 Apr 2024cs.CL cs.HC cs.ROcited by 0

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Abstract (arXiv)

Automated Speech Recognition shows superhuman performance for adult English speech on a range of benchmarks, but disappoints when fed children's speech. This has long sat in the way of child-robot interaction. Recent evolutions in data-driven speech recognition, including the availability of Transformer architectures and unprecedented volumes of training data, might mean a breakthrough for child speech recognition and social robot applications aimed at children. We revisit a study on child speech recognition from 2017 and show that indeed performance has increased, with newcomer OpenAI Whisper doing markedly better than leading commercial cloud services. Performance improves even more in highly structured interactions when priming models with specific phrases. While transcription is not perfect yet, the best model recognises 60.3% of sentences correctly barring small grammatical differences, with sub-second transcription time running on a local GPU, showing potential for usable autonomous child-robot speech interactions.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 4 of its 13 references that are in the map. First posted on arXiv 26 Apr 2024.

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References · 4

  1. 2022Robust Speech Recognition via Large-Scale Weak Supervisioncited by 3,972
  2. 2019Quantifying the Carbon Emissions of Machine Learningcited by 516
  3. 2017The Microsoft 2017 Conversational Speech Recognition Systemcited by 51
  4. 2023Transformers in Speech Processing: A Surveycited by 38

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