Clustering of disfluencies in typical, fast and cluttered speech

Bóna, Judit

doi:10.1080/02699206.2018.1513075

Cited by 12 publications

(8 citation statements)

References 23 publications

(36 reference statements)

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“…Literature on these distributional issues is much more scarce, some few exceptions to be mentioned include e.g. [Crible et al 2017], [Betz et al 2015], [Betz and Kosmala 2019], [Bóna 2019]. Our paper is in line with this distributional approach, which we advocate and check against Russian data.…”

Section: Introductionsupporting

confidence: 73%

“…Overall, five adjacent disfluency tokens precede a stretch of fluent speech. We consider the opposition of isolated vs. clustered disfluencies significant, as the latter type presumably indicates more severe difficulties than the former (see, e.g., [Robb et al 2009]; [Bóna 2019] for clinical accounts on clustering). However, there is no clear-cut between these two types.…”

Section: Isolated Vs Clustered Disfluenciesmentioning

confidence: 99%

See 1 more Smart Citation

Disfluencies in Russian Spoken Monologues: A Distributional Analysis

Korotaev¹,

Podlesskaya²,

Смирнова³

et al. 2020

Computational Linguistics and Intellectual Technologies

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The paper addresses the overall distribution of speech disfluencies in Russian spoken monologic discourse: basing on corpus data, we investigate qualitatively and quantitatively how disfluencies of different types group (or do not group) with each other and how isolated disfluencies and their sequences are sandwiched with periods of fluent speech in the course of speech production. Self-repairs, filled and silent pauses, and instances of hesitation lengthening were annotated in a subcorpus of the “Russian Pears Chats and Stories” (RUPEX). A distribution-oriented typology of disfluencies was proposed that distinguishes between isolated disfluencies, disfluency clusters, and quasiclusters. We claim that disfluency tokens tend to cluster, as isolated occurrences are significantly less frequent in our data than it could have been expected basing on the relative frequency of tokens. This finding contradicts previous studies that treated disfluency clusters as a more marginal phenomenon, and emphasizes the importance of a distributional, rather than merely structural, approach to annotating disfluencies. Furthermore, individual types of disfluency tokens demonstrate significantly different distributional patterns. Compared to other types, self-repairs occur more often in isolation, while words with hesitation lengthening appear predominantly in clusters, and filled pauses most often group with silent pauses to form quasi-clusters.

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Section: Introductionsupporting

confidence: 73%

Section: Isolated Vs Clustered Disfluenciesmentioning

confidence: 99%

Disfluencies in Russian Spoken Monologues: A Distributional Analysis

Korotaev¹,

Podlesskaya²,

Смирнова³

et al. 2020

Computational Linguistics and Intellectual Technologies

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“…Further, Garnett and St. Louis (2010) also reported twice as many disfluencies in PWC's speech than in the speech of typical speakers. Several studies, however, found no significant differences between PWC and typical speakers in the frequency of all disfluencies (Bakker et al, 2011;Myers et al, 2012;Bóna, 2016Bóna, , 2018. Contradictory results might emerge due to the small number of participants and large individual characteristics.…”

Section: Introductionmentioning

confidence: 92%

Effects of speech rate changes on pausing and disfluencies in cluttering

Pap¹

2019

Proceedings of DiSS 2019

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People with cluttering (PWC) often receive feedback, such as "Slow down!", even so, this fluency disorder cannot be cured by only slowing down the speakers' speech rate. When PWC accelerate their speech rate, language planning difficulties and word structure errors might occur, which might result in breakdowns in fluency and/or intelligibility. In the present paper characteristics of the frequency of disfluencies were examined in four different speech tasks from deliberately slow to maximum speech rate, whether speech rate changes have effects on cluttered speech. Twenty participants of this investigation were individuals suspected of cluttering with ages between 20 and 50 years of both genders. The results show that PWC are able to change, not only their speech rate but articulatory rate as well. Moreover, disfluencies were produced the most frequently in the speech task of maximum speech rate, where PWC do not have enough time for speech planning. The research provides empirical, measured data for a better insight into the nature of cluttering. Understanding the correlation between speech rate and disfluencies in cluttered speech is fundamental to improve the diagnosis of cluttering.

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“…Existing studies of disfluency clusters are mostly based on data from children with developmental stuttering (LaSalle & Huffman, 2015;Sawyer & Yairi, 2010) and from adults with persistent stuttering (Robb et al, 2009) or cluttering (Bóna, 2018(Bóna, , 2019Myers et al, 2012Myers et al, , 2008. There are only a couple studies on disfluency clusters in typical adult speakers (Bóna, 2018(Bóna, , 2019Myers et al, 2012), and even rarer are studies on disfluency clusters in atypical speech without classical fluency disorders . Myers et al (2012) investigated disfluencies and disfluency clusters in fluent adults and in adults with developmental cluttering (PWC).…”

Section: Disfluency Clustersmentioning

confidence: 99%

Disfluency clusters in typical and atypical finnish adult speech. A pilot study

Penttilä

Korpijaakko‐Huuhka

Bóna

2021

Clinical Linguistics & Phonetics

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This study first aimed to investigate disfluency clusters in typical and atypical Finnish adult speakers. Secondly, it aimed to observe possible fluency strategies in speakers representing different fluency levels. In addition to individual disfluency types, we examined different characteristics of disfluency clusters produced by 23 speakers in a fluency continuum. Three adult speaker groups participated in this study: typical speakers with high disfluency frequencies (GA), typical and atypical speakers with very high disfluency frequencies (GB) and atypical speakers with the highest disfluency frequencies (GC). Data were based on a narrative speech task, and disfluency clusters were analysed with both traditional methods and alternative methods. Two statistically significant differences between the speaker groups were found: 1) the length of the clusters was highest in GC compared to other groups, and 2) speakers in GC formulated their utterances more than other groups. Other results, although nonsignificant, were that 3) speakers in GA revised utterances more often than interrupted them compared to GB and GC speakers, and 4) clusters using repetitive words and phrases to maintain fluency were found in GA and GB only. In this study, different fluency levels revealed different strategies in both the production of single disfluencies and in disfluency clusters. It seems that more fluent speakers formulate their messages differently than less fluent speakers, and repetitions can be used to maintain fluency and possibly prevent difficult clusters, as noted with more fluent speakers.

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Clustering of disfluencies in typical, fast and cluttered speech

Cited by 12 publications

References 23 publications

Disfluencies in Russian Spoken Monologues: A Distributional Analysis

Disfluencies in Russian Spoken Monologues: A Distributional Analysis

Effects of speech rate changes on pausing and disfluencies in cluttering

Disfluency clusters in typical and atypical finnish adult speech. A pilot study

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