Analysis of Disfluency in Children's Speech
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Abstract (arXiv)
Disfluencies are prevalent in spontaneous speech, as shown in many studies of adult speech. Less is understood about children's speech, especially in pre-school children who are still developing their language skills. We present a novel dataset with annotated disfluencies of spontaneous explanations from 26 children (ages 5--8), interviewed twice over a year-long period. Our preliminary analysis reveals significant differences between children's speech in our corpus and adult spontaneous speech from two corpora (Switchboard and CallHome). Children have higher disfluency and filler rates, tend to use nasal filled pauses more frequently, and on average exhibit longer reparandums than repairs, in contrast to adult speakers. Despite the differences, an automatic disfluency detection system trained on adult (Switchboard) speech transcripts performs reasonably well on children's speech, achieving an F1 score that is 10% higher than the score on an adult out-of-domain dataset (CallHome).
Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). First posted on arXiv 8 Oct 2020.
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Citing papers per year: 2024: 1; 2025: 2; 2026: 3.
6 papers.
- 2025Children's Voice Privacy: First Steps And Emerging Challengescited by 5
- 2024Children's Speech Recognition through Discrete Token Enhancementcited by 3
- 2025K-Function: Joint Pronunciation Transcription and Feedback for Evaluating Kids Language Functioncited by 1
- 2026Beyond Length: Context-Aware Expansion and Independence as Developmentally Sensitive Evaluation in Child Utterancescited by 0
- 2026How Well Do Self-Supervised Speech Models Encode Age and Gender in Children's Speech? A Layer-Wise Analysis Across Multiple Architecturescited by 0
- 2026Deep Learning Techniques for Phoneme Recognition in Italian Children' s Speechcited by 0
- 2026Deep Learning Techniques for Phoneme Recognition in Italian Children' s Speech27 Sep 2026
- 2026How Well Do Self-Supervised Speech Models Encode Age and Gender in Children's Speech? A Layer-Wise Analysis Across Multiple Architectures20 Jun 2026
- 2026Beyond Length: Context-Aware Expansion and Independence as Developmentally Sensitive Evaluation in Child Utterances5 Feb 2026
- 2025K-Function: Joint Pronunciation Transcription and Feedback for Evaluating Kids Language Function3 Jul 2025
- 2025Children's Voice Privacy: First Steps And Emerging Challenges30 May 2025
- 2024Children's Speech Recognition through Discrete Token Enhancement19 Jun 2024