Abstract

Evaluations of letter naming and letter sounding are commonly used to measure a young child's growing reading ability, since performance in them is well‐correlated with future reading development. Assessing a child's oral reading skills requires teachers, as well as technologies that attempt to automate such assessment, to form an item‐level accept/reject decision based on speech cues and prior knowledge of the child's literacy level and linguistic background. With data collected from 171 K‐2 children, both learners and native speakers of American English, we designed and evaluated an automated letter naming assessment method using a simple word‐loop HMM decoding for the word‐level letter names. The automated accept/reject evaluation performance, 81.9%, approached the agreement of human raters, 83.2% (0.62 kappa). However, the task where children must produce the sound that the letter …

Date

2008

Authors

Shrikanth Narayanan, A Kazemzadeh, Matthew Black, Joseph Tepperman, Sungbok Lee, Abeer Alwan

Journal

The Journal of the Acoustical Society of America

Volume

123

Issue

5_Supplement

Pages

3327-3327

Publisher

Acoustical Society of America