Transitioning from analog to digital audio recording in childhood speech sound disorders

Few empirical findings or technical guidelines are available on the current transition from analog to digital audio recording in childhood speech sound disorders. Of particular concern in the present context was whether a transition from analog- to digital-based transcription and coding of prosody and voice features might require re-standardizing a reference database for research in childhood speech sound disorders. Two research transcribers with different levels of experience glossed, transcribed, and prosody-voice coded conversational speech samples from eight children with mild to severe speech disorders of unknown origin. The samples were recorded, stored, and played back using representative analog and digital audio systems. Effect sizes calculated for an array of analog versus digital comparisons ranged from negligible to medium, with a trend for participants’ speech competency scores to be slightly lower for samples obtained and transcribed using the digital system. We discuss the implications of these and other findings for research and clinical practice

Data-driven subclassification of speech sound disorders in preschool children

Purpose: The purpose of the study was to determine whether distinct subgroups of preschool children with speech sound disorders (SSD) could be identified using a subgroup discovery algorithm (SUBgroup discovery via Alternate Random Processes, or SUBARP). Of specific interest was finding evidence of a subgroup of SSD exhibiting performance consistent with atypical speech motor control

Distinct developmental profiles in typical speech acquisition

Three- to five-year-old children produce speech that is characterized by a high level of variability within and across individuals. This variability, which is manifest in speech movements, acoustics, and overt behaviors, can be input to subgroup discovery methods to identify cohesive subgroups of speakers or to reveal distinct developmental pathways or profiles. This investigation characterized three distinct groups of typically developing children and provided normative benchmarks for speech development. These speech development profiles, identified among 63 typically developing preschool-aged speakers (ages 36–59 mo), were derived from the children\u27s performance on multiple measures. These profiles were obtained by submitting to a k-means cluster analysis of 72 measures that composed three levels of speech analysis: behavioral (e.g., task accuracy, percentage of consonants correct), acoustic (e.g., syllable duration, syllable stress), and kinematic (e.g., variability of movements of the upper lip, lower lip, and jaw). Two of the discovered group profiles were distinguished by measures of variability but not by phonemic accuracy; the third group of children was characterized by their relatively low phonemic accuracy but not by an increase in measures of variability. Analyses revealed that of the original 72 measures, 8 key measures were sufficient to best distinguish the 3 profile groups