Abstract
Children with speech disorders often present with systematic speech error patterns. In clinical assessments of speech disorders, evaluating the severity of the disorder is central. Current measures of severity have limited sensitivity to factors like the frequency of the target sounds in the child’s language and the degree of phonological diversity, which are factors that can be assumed to affect intelligibility. By constructing phonological filters to simulate eight speech error patterns often observed in children, and applying these filters to a phonologically transcribed corpus of 350K words, this study explores three quantitative measures of phonological impact: Percentage of Consonants Correct (PCC), edit distance, and degree of homonymy. These metrics were related to estimated ratings of severity collected from 34 practicing clinicians. The results show an expected high correlation between the PCC and edit distance metrics, but that none of the three metrics align with clinicians’ ratings. Although these results do not generate definite answers to what phonological factors contribute the most to (un)intelligibility, this study demonstrates a methodology that allows for large-scale investigations of the interplay between phonological errors and their impact on speech in context, within and across languages.
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