Analysis of Disfluency in Children's Speech

TL;DR

This paper introduces a new dataset of children's spontaneous speech with annotated disfluencies, analyzes differences from adult speech, and evaluates an automatic disfluency detection system's performance across domains.

Contribution

It provides the first detailed analysis of disfluencies in preschool children's speech and assesses the cross-domain applicability of adult-trained detection systems.

Findings

Children have higher disfluency and filler rates than adults.

Nasal filled pauses are more common in children's speech.

An adult-trained disfluency detection system performs reasonably well on children's speech.

Abstract

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).