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Τίτλος: The implementation of the 'Testing of Phonological Skills (TOPS)' tool: a computer-based phonological analysis algorithm
Συγγραφείς: Armostis, Spyros 
Petinou, Kakia 
Kyprianou, Anna 
Major Field of Science: Medical and Health Sciences
Field Category: Health Sciences
Λέξεις-κλειδιά: algorithm;Computer-based phonological analysis;cross-linguistic;phonetic analysis
Ημερομηνία Έκδοσης: 17-Οκτ-2022
Πηγή: Clinical Linguistics and Phonetics, 2023, vol.37 n.11, pp.1030-1049
Volume: 37
Issue: 11
Start page: 1030
End page: 1049
Περιοδικό: Clinical Linguistics & Phonetics 
Περίληψη: A computer-based algorithm was used for phonological analysis of Cypriot Greek (CG) word productions elicited from a sample of typically developing (TD) CG-speaking children. Specific focus was on (a) creating a complete CG phonetic and phonological test; (2) implementing a novel computer-based algorithm in the analysis of selected speech stimuli from CG-speaking TD children; and (3) examining independent and relational speech patterns based on the computer-based algorithm. The probe word list consisted of 182 target words and included all CG consonants in all word positions. Normative data were collected on a representative sample of 20 TD CG-speaking children aged 3;0 to 6;0 years. Productions were phonetically transcribed and inserted into the computer algorithm for automatic data reduction of measurable dependent variables including the percentage of consonants correct (PCC), phonetic inventory size (PIS), word-initial onset deletion (IOD), and Regressive Assimilation (RASS). Correlation analyses revealed significant interactions among phonetic and phonological patterns as well as predictive relationships of PCC and segmental word-position. The implementation of this specific probe word list permitted a homogeneous and inclusive sampling analysis. Participants presented specific developmental trajectories of segmental and phonological patterns as a function of age.
URI: https://hdl.handle.net/20.500.14279/29800
ISSN: 02699206
DOI: 10.1080/02699206.2022.2132422
Rights: © Taylor & Francis Group, LLC.
Type: Article
Affiliation: University of Cyprus 
Cyprus University of Technology 
Publication Type: Peer Reviewed
Εμφανίζεται στις συλλογές:Άρθρα/Articles

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