Linguistic Features of Stuttering During Spontaneous Speech

• Published in: Journal of fluency disorders 2023-12, Vol.78, p.106016-106016, Article 106016
• Main Authors: Warner, Haley J., Shroff, Ravi, Zuanazzi, Arianna, Arenas, Richard M., Jackson, Eric S.
• Format: Article
• Language: English
• Subjects: linguistics; spontaneous speech; stuttering
• ISSN: 0094-730X; 1873-801X
• DOI: 10.1016/j.jfludis.2023.106016

Previous work shows that linguistic features (e.g., word length, word frequency) impact the predictability of stuttering events. Most of this work has been conducted using reading tasks. Our study examined how linguistic features impact the predictability of stuttering events during spontaneous speech. The data were sourced from the FluencyBank database and consisted of interviews with 35 adult stutterers (27,009 words). Three logistic regression mixed models were fit as the primary analyses: one model with four features (i.e., initial phoneme, grammatical function, word length, and word position within a sentence), a second model with six features (i.e., the features from the previous model plus word frequency and neighborhood density), and a third model with nine features (i.e., the features from the previous model plus bigram frequency, word concreteness, and typical age of word acquisition). We compared our models using the Area Under the Curve statistic. The four-feature model revealed that initial phoneme, grammatical function, and word length were predictive of stuttering events. The six-feature model revealed that initial phoneme, word length, word frequency and neighborhood density were predictive of stuttering events. The nine-feature model was not more predictive than the six-feature model. Linguistic features that were previously found to be predictive of stuttering during reading were predictive of stuttering during spontaneous speech. The results indicate the influence of linguistic processes on the predictability of stuttering events such that words associated with increased planning demands (e.g., longer words, low frequency words) were more likely to be stuttered. •Linguistic features are predictive of stuttering during spontaneous speech.•Six linguistic features better predicted stuttering than four features.•Nine linguistic features were not more predictive of stuttering than six features.