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There is little research on the production of speech disfluencies such as silent pauses, repetitions, self-corrections, and filled pauses (e.g., eh , em ) in monolingual autistic children, and there is no data on this crucial part of speech production in bilingual autistic children. This study aims to address this gap by examining disfluency production in bilingual autistic and non-autistic children across two linguistically distinct languages, HL-Russian (the home language) and SL-Hebrew (the societal language). Fifty-one bilingual Russian-Hebrew-speaking autistic and non-autistic children aged 5–9 (autistic: n  = 21; non-autistic: n  = 30), matched for age and non-verbal intelligence, participated in picture-based story-generation tasks (LITMUS MAIN, Gagarina et al., ZAS Papers in Linguistics, 63:1–36, 2019). Audio recordings of narrative samples were transcribed, coded, and scored for eleven disfluency types using CLAN tools. The non-autistic group produced higher overall disfluency rate than the autistic group. The autistic group exhibited fewer filled and silent pauses than the non-autistic group in HL-Russian. Furthermore, non-autistic children manifested varied distribution of disfluency types across languages, while autistic children displayed more consistent patterns across languages. In summary, we replicated findings from previous research on monolinguals only partly, as no between-group difference in filled pauses was found in SL-Hebrew. Additionally, bilingual autistic children exhibited language-universal patterns of disfluency production, whereas their non-autistic peers displayed language-specific patterns.

Disfluency can occur when a speaker faces difficulty in language production, but it is also as a strategy to stall for time and create an illusion of continuity in speech. To better understand the origin of disfluency, the current study used a drift diffusion model (DDM) in a context of semantic competition. We developed a speeded version of the picture–word interference paradigm, in which participants name pictures while ignoring distractor words. We applied the DDM approach to data from related vs. unrelated distractors but also from fluent versus disfluent answers in the related condition (e.g., “apple” vs. “hm... a-apple”). All differences between conditions were mapped onto the drift rate parameter. Unrelated distractor words resulted in a higher drift rate compared with semantic distractors, and correct fluent answers resulted in a higher drift rate compared with correct disfluent answers. Our findings suggest that semantic interference taps into the process of spreading activation through the lexical-semantic system. Most importantly, disfluency in the picture-naming task reflects competition between response options and is not a strategy from the speaker to stall for time to accurately name the picture.

This paper analyses disfluencies and ungrammatical expressions in the speech of 11–13-year-old Finnish-speaking boys with ASD (N = 5) and with neurotypical development (N = 6). The ASD data were from authentic group therapy sessions and neurotypical data from teacher-led group discussions. The proportion of disfluencies and ungrammatical expressions was greater in the speech of participants with ASD (26.4%) than in the control group (15.5%). Furthermore, a qualitative difference was noted: The ASD group produced long, complex disfluent turns with word searches, self-repairs, false starts, fillers, prolongations, inconsistent syntactic structures and grammatical errors, whereas in the control group, the disfluencies were mainly fillers and sound prolongations. The disfluencies and ungrammatical expressions occurring in the ASD participants’ interactions also caused comprehension problems.

Filler disfluencies— uh and um —are thought to serve distinct discourse functions. We examined fillers in spontaneous speech by youth with autism spectrum disorder (ASD), who struggle with pragmatic language, and by youth with ASD who have achieved an ‘optimal outcome’ (OO), as well as in peers with typical development (TD). While uh rates did not differ, participants with ASD produced um less frequently than OO or TD groups. Um rate was associated with autism symptom severity, but not executive function or language abilities, suggesting that um serves a pragmatic, listener-oriented function. Moreover, in contrast to minimal production in ASD, the typical OO um production substantiates the normalization of subtle social communication in this population.

In the current study, we asked whether delays in the earliest stages of picture naming elicit disfluency. To address this question, we used a network task, where participants describe the route taken by a marker through visually presented networks of objects. Additionally, given that disfluencies are arguably multifactorial, we combined this task with eye tracking, to be able to disentangle disfluency related to word preparation from other factors (e.g., stalling strategy). We used visual blurring, which hinders visual identification of the items and thereby slows down selection of a lexical concept. We tested the effect of this manipulation on disfluency production and visual attention. Blurriness did not lead to more disfluency on average and viewing times decreased with blurred pictures. However, multivariate pattern analyses revealed that a classifier could predict above chance, from the pattern of disfluency, whether each participant was about to name blurred or control pictures. Impeding the conceptual generation of a message therefore affected the pattern of disfluencies of each participant individually, but this pattern was not consistent from one participant to another. Additionally, some of the disfluency and eye-movement variables correlated with individual cognitive differences, in particular with inhibition.

To writing anything on a keyboard at all requires us to know first what to type, then to activate motor programmes for finger movements, and execute these. An interruption in the information flow at any of these stages leads to disfluencies. To capture this combination of fluent typing and typing hesitations, researchers calculate different measures from keystroke-latency data—such as mean inter-keystroke interval and pause frequencies. There are two fundamental problems with this: first, summary statistics ignore important information in the data and frequently result in biased estimates; second, pauses and pause-related measures are defined using threshold values which are, in principle, arbitrary. We implemented a series of Bayesian models that aimed to address both issues while providing reliable estimates for individual typing speed and statistically inferred process disfluencies. We tested these models on a random sample of 250 copy-task recordings. Our results illustrate that we can model copy typing as a mixture process of fluent and disfluent key transitions. We conclude that mixture models (1) map onto the information cascade that generate keystrokes, and (2) provide a principled approach to detect disfluencies in keyboard typing.

Purpose: The purpose of this study is to investigate how epidemiological and clinical factors collectively predict whether a preschooler who is stuttering will persist or recover and to provide guidance on how clinicians can use these factors to evaluate a child's risk for stuttering persistence. Method: We collected epidemiological and clinical measures from 52 preschoolers (M = 54.4 months, SD = 6.7 months; 38 boys and 14 girls) diagnosed as stuttering. We then followed these children longitudinally to document whether they eventually recovered or persisted in stuttering. Risk factors found to be significantly associated with stuttering persistence were used to build single and multiple variable predictive statistical models. Finally, we assessed each model's prediction capabilities by recording how accurate a model was in predicting a child's stuttering outcome--persisting or recovered. Results: We found that a positive family history of stuttering, poorer performance on a standardized articulation/phonological assessment, higher frequency of stuttering-like disfluencies during spontaneous speech, and lower accuracy on a nonword repetition task were all significantly associated with an increased probability of persistence. The interaction between family history of stuttering and nonword repetition performance was also significant. The full multiple regression model incorporating all these risk factors resulted in the best fitting model with the highest predictive accuracy and lowest error rate. Conclusions: For the first time, we show how multiple risk factors collectively predict the probability of stuttering persistence in 3- to 5-year-old preschool children who stutter. Using the full combination of risk factors to assess preschoolers who stutter yielded more accurate predictions of persistence compared to sparser models. A better understanding of the factors that underlie stuttering persistence will yield insight into the underpinnings of chronic stuttering and will help identify etiological targets for novel treatment approaches.

Purpose: Stuttering is characterized by intermittent speech disfluencies, which are dramatically reduced when speakers synchronize their speech with a steady beat. The goal of this study was to characterize the neural underpinnings of this phenomenon using functional magnetic resonance imaging. Method: Data were collected from 16 adults who stutter and 17 adults who do not stutter while they read sentences aloud either in a normal, self-paced fashion or paced by the beat of a series of isochronous tones (\"rhythmic\"). Task activation and task-based functional connectivity analyses were carried out to compare neural responses between speaking conditions and groups after controlling for speaking rate. Results: Adults who stutter produced fewer disfluent trials in the rhythmic condition than in the normal condition. Adults who stutter did not have any significant changes in activation between the rhythmic condition and the normal condition, but when groups were collapsed, participants had greater activation in the rhythmic condition in regions associated with speech sequencing, sensory feedback control, and timing perception. Adults who stutter also demonstrated increased functional connectivity among cerebellar regions during rhythmic speech as compared to normal speech and decreased connectivity between the left inferior cerebellum and the left prefrontal cortex. Conclusions: Modulation of connectivity in the cerebellum and prefrontal cortex during rhythmic speech suggests that this fluency-inducing technique activates a compensatory timing system in the cerebellum and potentially modulates top-down motor control and attentional systems. These findings corroborate previous work associating the cerebellum with fluency in adults who stutter and indicate that the cerebellum may be targeted to enhance future therapeutic interventions.

Purpose The purpose of this meta-analytic study was to identify clinical characteristics, defined as child factors that can be assessed by a speech-language pathologist as part of a routine speech-language evaluation that may differentiate children who persist in stuttering from children who eventually recover from stuttering. Clinical characteristics explored included sex, age at onset, family history of stuttering, stuttering frequency and severity, speech-language skills, and temperament. Method Studies were identified through electronic databases, journals, and reference lists of relevant reports (e.g., research articles). Eligible studies followed young children who stutter (i.e., under 6 years old) for at least 24 months, assessed a potential clinical marker at study entry, and determined talker group classification (i.e., persistent or recovered) at study completion. Sex and family history differences were estimated using risk ratios; all other differences were estimated using Hedges's . Heterogeneity and methodological differences among studies were evaluated. Results Eleven studies (41 reports) met eligibility criteria. Persistent children were older at stuttering onset and exhibited higher frequencies of stuttering-like disfluencies, lower speech sound accuracy, and lower expressive and receptive language skills than recovered children. Males and children with a family history of stuttering were also more likely to persist. Conclusions Clinical characteristics were identified that are associated with increased risk for stuttering persistence. Future studies have the potential to translate these clinical characteristics into prognostic markers for stuttering persistence risk.

Previous research suggests that English monolingual children and adults can use speech disfluencies (e.g., uh) to predict that a speaker will name a novel object. To understand the origins of this ability, we tested 48 32-month-old children (monolingual English, monolingual French, bilingual English–French; Study 1) and 16 adults (bilingual English–French; Study 2). Our design leveraged the distinct realizations of English (uh) versus French (euh) disfluencies. In a preferential-looking paradigm, participants saw familiar–novel object pairs (e.g., doll–rel), labeled in either Fluent (“Look at the doll/rel!”), Disfluent Language-consistent (“Look at thee uh doll/rel!”), or Disfluent Language-inconsistent (“Look at thee euh doll/rel!”) sentences. All participants looked more at the novel object when hearing disfluencies, irrespective of their phonetic realization. These results suggest that listeners from different language backgrounds harness disfluencies to comprehend day-to-day speech, possibly by attending to their lengthening as a signal of speaker uncertainty. Stimuli and data are available at .