Automatic detection and classification of disfluent reading miscues in young children's speech for the purpose of assessment

This paper explores the importance of disfluent reading miscues (sounding-out, hesitations, whispering, elongated onsets, question intonations) in automating the assessment of children’s oral word reading tasks. Analysis showed that a significant portion (21%) of the speech obtained from grades K-2 children from predominantly Spanish-speaking families contained at least one disfluent reading miscue. We discovered human evaluators rated the fluency nearly as important as accuracy when judging the overall reading ability of a child. We devised a lexical method for automatically detecting the sounding-out, hesitation, and whispering disfluencies, which achieved a 14.9% missed detection and 8.9% false alarm rate. We were also able to discriminate 69.4% of the sound-outs from other disfluencies with a 28.5% false alarm rate, a promising and novel result.