Disfluency
- LAST REVIEWED: 18 August 2022
- LAST MODIFIED: 22 February 2018
- DOI: 10.1093/obo/9780199772810-0189
- LAST REVIEWED: 18 August 2022
- LAST MODIFIED: 22 February 2018
- DOI: 10.1093/obo/9780199772810-0189
Introduction
Disfluencies are interruptions in the regular flow of speech, such as using uh and um, pausing silently, repeating words, or interrupting oneself to correct something said previously. Disfluency can be distinguished from speech errors in which the speaker produces the wrong words or speech sounds but may do so without any interruptions in the flow of speech. Disfluencies commonly stem from delays or errors in the cognitive processes of language production, although some studies indicate that social or other cognitive factors may play a role too. Even in non-disordered speech, disfluency is common and thus relevant to general theories of language production and comprehension. However, the frequency and types of disfluency may also be influenced by various clinical diagnoses (sometimes separately termed “dysfluency”); these include most notably stuttering, but also attention deficit / hyperactive disorder and autism spectrum disorders. Children’s speech also includes disfluencies, but disfluency does not necessarily indicate poor language acquisition; in fact, some disfluencies are used more by children who are at a more advanced stage of linguistic or conceptual development. Some work has considered whether certain disfluencies—namely, fillers such as uh and um—should be considered deliberate signals produced by a speaker to indicate having momentary trouble with language production, but this hypothesis remains debated. Although disfluencies interrupt the flow of speech, they do not necessarily impair comprehension; in fact, many studies have observed that disfluency can even facilitate comprehension in some situations, because disfluencies increase attention to the speech stream or because they allow a listener to predict that the speaker will next refer to something difficult. However, when speakers correct themselves, the original, erroneous material is not always completely forgotten by hearers, and there are lingering effects in comprehension of the original material. Moreover, disfluency can present a challenge both for automated speech-recognition systems and text-to-speech systems, and many computational studies have examined models for detecting and accommodating disfluency.
General Overviews
Several articles have reviewed the disfluency literature, with varying aims. Ferreira and Bailey 2004 reviews the comprehension of disfluent speech and its consequences for syntactic processing. Corley and Stewart 2008 reviews the literature on filled pauses in particular, and the authors use the literature to argue against the claim that filled pauses constitute a deliberate linguistic signal. Lickley 2015 provides an overview of disfluency in production, while emphasizing the difference in the definitions of fluency used within specific atypical populations.
Corley, M., and O. W. Stewart. 2008. Hesitation disfluencies in spontaneous speech: The meaning of um. Language and Linguistics Compass 2.4: 589–602.
DOI: 10.1111/j.1749-818X.2008.00068.x
Clear review of production and comprehension of filled pauses such as um. On the basis of this evidence, presents the argument that filled pauses do not constitute deliberately planned linguistic signals.
Ferreira, F., and K. G. D. Bailey. 2004. Disfluencies and human language comprehension. Trends in Cognitive Sciences 8.5: 231–237.
DOI: 10.1016/j.tics.2004.03.011
Provides an accessible introduction to disfluencies and a short review of the comprehension of disfluent speech. Has a particular focus on syntactic processing of disfluent speech.
Lickley, R. J. 2015. Fluency and disfluency. In The handbook of speech production. Edited by M. A. Redford, 445–474. Blackwell Handbooks in Linguistics. Malden, MA: Wiley-Blackwell.
DOI: 10.1002/9781118584156.ch20
Reviews fluency in typical healthy adult speech production. Illustrates how fluency is defined within a given population (e.g., stutterers, aphasics, second-language learners).
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