mlsanityData to 7 Oct 2026

Automatic Speech Recognition of Non-Native Child Speech for Language Learning Applications

arXiv 2306.16710 ↗First posted 29 Jun 2023cs.CL cs.SD eess.AScited by 3

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Abstract (arXiv)

Voicebots have provided a new avenue for supporting the development of language skills, particularly within the context of second language learning. Voicebots, though, have largely been geared towards native adult speakers. We sought to assess the performance of two state-of-the-art ASR systems, Wav2Vec2.0 and Whisper AI, with a view to developing a voicebot that can support children acquiring a foreign language. We evaluated their performance on read and extemporaneous speech of native and non-native Dutch children. We also investigated the utility of using ASR technology to provide insight into the children's pronunciation and fluency. The results show that recent, pre-trained ASR transformer-based models achieve acceptable performance from which detailed feedback on phoneme pronunciation quality can be extracted, despite the challenging nature of child and non-native speech.

Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). Builds on 3 of its 17 references that are in the map. First posted on arXiv 29 Jun 2023.

Builds on

3 of 17 references.

References · 3

  1. 2022Robust Speech Recognition via Large-Scale Weak Supervisioncited by 3,972
  2. 2020wav2vec 2.0: A Framework for Self-Supervised Learning of Speech Representationscited by 3,853
  3. 2023WhisperX: Time-Accurate Speech Transcription of Long-Form Audiocited by 320

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 1; 2024: 1; 2025: 0; 2026: 1.

3 papers.