Profiling Speech Sound Disorders for Clinical Validation of the Computer Articulation Instrument

Haaften, Leenke van; Diepeveen, Sanne; Terband, Hayo; Vermeij, Bernadette; Engel-Hoek, Lenie van den; Swart, Bert de; Maassen, Ben

doi:10.1044/2018_ajslp-msc18-18-0112

Cited by 8 publications

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“…No previous studies reported PCC-R and PVC for typically developing Dutch-speaking children despite the fact that these measures are widely used to support the diagnosis of SSDs (McLeod and Crowe, 2018), where PCC-R is most relevant to determine the severity of involvement (Shriberg et al, 1997). The norm scores were derived from the items of the picture-naming task of the CAI (Maassen et al, 2019), whose psychometric properties were verified, with our earlier studies revealing sufficient interrater reliability, test-retest reliability, and construct validity (Van Haaften et al, 2019a), and supported known-group validity (Van Haaften et al, 2019b). The CAI has since been made available for use in Dutch clinical practice.…”

Section: Discussionmentioning

confidence: 88%

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Speech sound development in typically developing 2–7‐year‐old Dutch‐speaking children: A normative cross‐sectional study

Haaften

Diepeveen

Engel-Hoek

et al. 2020

Intl J Lang & Comm Disor

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Background Dutch is a West‐Germanic language spoken natively by around 24 million speakers. Although studies on typical Dutch speech sound development have been conducted, norms for phonetic and phonological characteristics of typical development in a large sample with a sufficient age range are lacking. Aim To give a detailed description of the speech sound development of typically developing Dutch‐speaking children from 2 to 7 years. Methods & Procedures A total of 1503 typically developing children evenly distributed across the age range of 2;0–6;11 years participated in this normative cross‐sectional study. The picture‐naming task of the Computer Articulation Instrument (CAI) was used to collect speech samples. Speech development was described in terms of (1) percentage consonants correct—revised (PCC‐R) and percentage vowels correct (PVC); (2) consonant, vowel and syllabic structure inventories; (3) degrees of complexity (phonemic feature hierarchy); and (4) phonological processes. Outcomes & Results A two‐way mixed analysis of variance (ANOVA) confirmed a significant increase in the number of PCC‐R and PVC between the ages of 2;0 and 6;11 years (p < 0.001). The consonant inventory was found to be complete at 3;7 years of age for the syllable‐initial consonants, with the exception of the voiced fricatives /v/ and /z/, and the liquid /r/. All syllable‐final consonants were acquired before age 4;4 years. At age 3;4 years, all children had acquired a complete vowel inventory, and at age 4;7 years they produced most syllable structures correctly, albeit that the syllable structure CCVCC was still developing. All phonological contrasts were produced correctly at 3;8 years of age. Children in the younger age groups used more phonological simplification processes than the older children, and by age 4;4 years, all had disappeared, except for the initial cluster reduction from three to two consonants and the final cluster reduction from two to one consonant. Conclusions & Implications This paper describes a large normative cross‐sectional study of Dutch speech sound development which, in clinical practice, can help Dutch speech–language pathologists to differentiate children with delayed or disordered speech development from typically developing children.

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Section: Discussionmentioning

confidence: 88%

“…2019a), and supported known‐group validity (Van Haaften et al . 2019b). The CAI has since been made available for use in Dutch clinical practice.…”

Section: Discussionmentioning

confidence: 99%

Speech sound development in typically developing 2–7‐year‐old Dutch‐speaking children: A normative cross‐sectional study

Haaften

Diepeveen

Engel-Hoek

et al. 2020

Intl J Lang & Comm Disor

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“…Regardless, the current study suggests profiling speech features during phonetically complex tasks may help characterize resolving motor speech impairments in children with a history of CAS when other tools, designed for children with higher levels SPEECH SOUND DEVELOPMENT IN CHILDREN of severity, are no longer sensitive to the subtleties of their impairment. 2 University of Zagreb, Zagreb, Croatia 3 University of Groningen, Groningen, The Netherlands Speech is a complex motor skill; its assessment carries clinical importance (Van Haaften et al, 2019). One of the few objective assessments of motor speech performance is diadochokinesis (DDK).…”

Section: Discussionmentioning

confidence: 99%

“…These stop-consonants /p/, /t/, and /k/ occur in most languages (Schwartz et al, 2012) and are among the first consonants acquired (McLeod & Crowe, 2018), their use in DDK allows a nearly universal application . In typically developing (TD) children, the DDK-rate is correlated with age and is viewed as an index of oral motor development (Van Haaften et al, 2019;Diepeveen et al, 2021). There is no uniform method of administrating the DDK or measuring the rate of the sequence(s) which leads to large variability of norm data and makes it difficult to compare between studies (Diepeveen et al, 2019).…”

Section: Discussionmentioning

confidence: 99%

Abstracts of the 8th International Conference on Speech Motor Control Groningen, August 2022

SSTP

2022

SSTP

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This Supplement of ‘Tijdschrift voor Stem-, Spraak- en Taalpathologie’ (Journal of Voice, Speech and Language Pathology) contains the abstracts of the eighth edition of the International Conference on Speech Motor Control, held in Groningen, The Netherlands, August 24 - 27, 2022. With this eighth conference, a well-established Nijmegen (5 editions) - Groningen (6th & 7th edition) tradition continues. This conference, like the ones before, highlights new trends and state-of-the-art approaches in theoretical and applied research in the area of normal and disordered speech motor control. The five years since the previous conference in 2017 have yielded not only further insights in genetic, neural, physiological and developmental aspects of speech production, stuttering and other speech motor conditions, but have also advanced theoretical modelling. Combined with ongoing studies of populations that are increasingly better characterized genetically and neurobiologically, this quantitative boost of interdisciplinary results is now leading to a qualitative turning point in which large data sets are analyzed with powerful artificial intelligence and machine learning algorithms. The implementation of theories into computational models allows for the explicit testing of multifactorial interactions, thereby going beyond the more traditional single-factor experiments. Machine learning and the data sharing required to make this feasible are a special topic of the 2022 conference.

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“…The five components from the norm group [ 13 ] were used in a previous study to compare the scores of 41 children with SSD [ 44 ]. That is, the components’ weights obtained from the PCA of the norm group were used to calculate component scores for the children with SSD.…”

Section: Discussionmentioning

confidence: 99%

Process-Oriented Profiling of Speech Sound Disorders

et al. 2022

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The differentiation between subtypes of speech sound disorder (SSD) and the involvement of possible underlying deficits is part of ongoing research and debate. The present study adopted a data-driven approach and aimed to identify and describe deficits and subgroups within a sample of 150 four to seven-year-old Dutch children with SSD. Data collection comprised a broad test battery including the Computer Articulation Instrument (CAI). Its tasks Picture Naming (PN), NonWord Imitation (NWI), Word and NonWord Repetition (WR; NWR) and Maximum Repetition Rate (MRR) each render a variety of parameters (e.g., percentage of consonants correct) that together provide a profile of strengths and weaknesses of different processes involved in speech production. Principal Component Analysis on the CAI parameters revealed three speech domains: (1) all PN parameters plus three parameters of NWI; (2) the remaining parameters of NWI plus WR and NWR; (3) MRR. A subsequent cluster analysis revealed three subgroups, which differed significantly on intelligibility, receptive vocabulary, and auditory discrimination but not on age, gender and SLPs diagnosis. The clusters could be typified as three specific profiles: (1) phonological deficit; (2) phonological deficit with motoric deficit; (3) severe phonological and motoric deficit. These results indicate that there are different profiles of SSD, which cover a spectrum of degrees of involvement of different underlying problems.

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Profiling Speech Sound Disorders for Clinical Validation of the Computer Articulation Instrument

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Cited by 8 publications

References 40 publications

Speech sound development in typically developing 2–7‐year‐old Dutch‐speaking children: A normative cross‐sectional study

Speech sound development in typically developing 2–7‐year‐old Dutch‐speaking children: A normative cross‐sectional study

Abstracts of the 8th International Conference on Speech Motor Control Groningen, August 2022

Process-Oriented Profiling of Speech Sound Disorders

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