Automated Analysis of Syllable Complexity as an Indicator of Speech Disorder (2017)

Marisha Speights, Joel MacAuslan, Noah Silbert, Suzanne Boyce
This study was designed to examine the feasibility of the Syllabic Cluster algorithm in the SpeechMark® MATLAB toolbox as an automated approach for identifying differences in speakers with and without Speech Sound Disorders(SSD).

Background

  • In the course of normal development, children master voluntary coordination of the motoric movements necessary for the utterance of complex syllables.
  • Development of well-formed syllables has been shown to be a significant predictor of later communication skills.
  • Children with delayed speech production show atypical trends in the mastery of well-formed syllables, especially in continuous speech.

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