Speech fluency in aphasics

Kreindler, A; Mihăilescu, L; Fradis, A

doi:10.1016/0093-934x(80)90140-6

Cited by 18 publications

(10 citation statements)

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“…and duration of pauses, complexity of syntax, and the integrity of the prosodic line (Deloche, Jean-Louis, & Seron, 1979;Feyereisen, Pillon, & Partz, 1991;Goodglass & Kaplan, 1983;Greenwald, Nadeau, & Rothi, 2000;Kerschensteiner, Poeck, & Brunner, 1972;Klein, Masur, Farber, Shinnar, & Rapin, 1992). Some authors recommend the use of total speaking time and the number of words produced to tell a story as additional measures of fluency (Kreindler, Mihailescu, & Fradis, 1980). Because of its multivariable composition, speech fluency is particularly difficult to quantify.…”

Section: Introductionmentioning

confidence: 97%

Speech Rate and Fluency in Children and Adolescents

Martins

Vieira

Loureiro

et al. 2007

Child Neuropsychology

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Reduced speech fluency is frequent in clinical paediatric populations, an unexplained finding. To investigate age related effects on speech fluency variables, we analysed samples of narrative speech (picture description) of 308 healthy children, aged 5 to 17 years, and studied its relation with verbal fluency tasks. All studied measures showed significant developmental effects. Speech rate and verbal fluency scores increased, while pauses, repetitions and locution time declined with age. Speech rate correlated with semantic fluency tasks suggesting that it also depends upon the efficacy of lexical retrieval. These results indicate that the interpretation of disorders of speech fluency in childhood must incorporate age appropriate norms.

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Section: Introductionmentioning

confidence: 97%

Speech Rate and Fluency in Children and Adolescents

Martins

Vieira

Loureiro

et al. 2007

Child Neuropsychology

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“…However, previous studies (Benson, 1967; Gordon, 2006; Kerschensteiner et al, 1972; Kreindler et al, 1980) investigated speech rate at the word level, suggesting a cutoff of 50 words per minute for nonfluent and 90 words per minute for fluent speech (Kerschensteiner et al, 1972). On the other hand, our study explored speech rate at the syllable level, since distorted words and neologisms would potentially eliminate some of the utterances (Feyereisen et al, 1986).…”

Section: Discussionmentioning

confidence: 98%

“…Fillmore (1979), for example, defined fluency as the facility to speak in a coherent, creative, semantically dense, and contextually appropriate manner in order to “fill time with talk”. Kreindler, Mihailescu, and Fradis (1980) presented an altogether different perspective, arguing that fluent speech is composed of many words produced over a long time period with a rapid rate. Finally, Goodglass and Kaplan (1983) defined language fluency as the ability to produce long, uninterrupted, and grammatically diverse runs of words that are easily articulated.…”

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confidence: 99%

“…Furthermore, a number of empirical differences exist across different studies, reflecting deviations in the use of terminology, scales for measurement, and derivation of values (e.g., speech rate calculation). The features that have differentiated fluent and nonfluent speech in previous studies include speech rate (e.g., Feyereisen, Verbeke-Dewitte, & Seron, 1986; Gordon, 2006; but see Wagenaar et al, 1975; Kreindler et al, 1980), proportion of words in sentences (e.g., Gordon, 2006), the number of words produced (e.g., Kreindler et al, 1980), phrase length (e.g., Goodglass, Quadfasel, & Timberlake, 1964), total speaking time (e.g., Feyereisen et al, 1986), speech initiation latency and overt struggle (e.g., Benson, 1967), and melodic line (e.g., Gordon, 1998). …”

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confidence: 99%

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Perceptual cues used by listeners to discriminate fluent from nonfluent narrative discourse

et al. 2011

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Background Language fluency is a common diagnostic marker for discriminating among aphasia subtypes and improving clinical inference about site of lesion. Nevertheless, fluency remains a subjective construct that is vulnerable to a number of potential sources of variability, both between and within raters. Moreover, this variability is compounded by distinct neurological aetiologies that shape the characteristics of a narrative speech sample. Previous research on fluency has focused on characteristics of a particular patient population. Less is known about the ways that raters spontaneously weigh different perceptual cues when listening to narrative speech samples derived from a heterogeneous sample of brain-damaged adults. Aim We examined the weighted contribution of a series of perceptual predictors that influence listeners’ judgements of language fluency among a diverse sample of speakers. Our goal was to sample a range of narrative speech representing most fluent (i.e., healthy controls) to potentially least nonfluent (i.e., left inferior frontal lobe stroke). Methods & Procedures Three raters blind to patient diagnosis made forced choice judgements of fluency (i.e., fluent or nonfluent) for 61 pseudorandomly presented narrative speech samples elicited by the BDAE Cookie Theft picture. Samples were collected from a range of clinical populations, including patients with frontal and temporal lobe pathologies and non-brain-damaged speakers. We conducted a logistic regression analysis in which the dependent measure was the majority judgement of fluency for each speech sample (i.e., fluent or non-fluent). The statistical model contained five predictors: speech rate, syllable type token ratio, speech productivity, audible struggle, and filler ratio. Outcomes & Results This statistical model fit the data well, discriminating group membership (i.e., fluent or nonfluent) with 95.1% accuracy. The best step of the regression model included the following predictors: speech rate, speech productivity, and audible struggle. Listeners were sensitive to different weightings of these predictors. Conclusions A small combination of perceptual variables can strongly discriminate whether a listener will assign a judgement of fluent versus nonfluent. We discuss implications for these findings and identify areas of potential future research towards further specifying the construct of fluency among adults with acquired speech and language disorders.

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“…This is partly because of the different weights given by examiners to different aspects of the problem. For example, some researchers have focused on the rate of speech, defining fluent speech as composed of many words produced over a long time period with a rapid rate (Kreindler, Mihailescu, & Fradis, 1980). Others have focused on both rate and syntactic complexity of the narrative (Goodglass & Kaplan, 1983; Wagenaar, Snow, & Prins, 1975).…”

Section: Introductionmentioning

confidence: 99%

Investigating the origin of nonfluency in aphasia: A path modeling approach to neuropsychology

Nozari

Faroqi‐Shah

2017

Cortex

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A major challenge in understanding the origin of clinical symptoms in neuropsychological impairments is capturing the complexity of the underlying cognitive structure. This paper presents a practical guide to path modeling, a statistical approach that is well-suited for modeling multivariate outcomes with a multi-factorial origin. We discuss a step-by-step application of such a model to the problem of nonfluency in aphasia. Individuals with aphasia are often classified into fluent and nonfluent groups for both clinical and research purposes, but despite a large body of research on the topic, the origin of nonfluency remains obscure. We propose a model of nonfluency inspired by the psycholinguistic approach to sentence production, review several bodies of work that have independently suggested a relationship between fluency and various elements in this model, and implement it using path modeling on data from 112 individuals with aphasia from the AphasiaBank. The results show that word production, comprehension, and working memory deficits all contribute to nonfluency, in addition to syntactic impairment which has a strong and direct impact on fluency. More generally, we demonstrate that a path model is an excellent tool for exploring complex neuropsychological symptoms such as nonfluency.

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Speech fluency in aphasics

Cited by 18 publications

References 5 publications

Speech Rate and Fluency in Children and Adolescents

Speech Rate and Fluency in Children and Adolescents

Perceptual cues used by listeners to discriminate fluent from nonfluent narrative discourse

Investigating the origin of nonfluency in aphasia: A path modeling approach to neuropsychology

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