We describe an approach to using speech recognition in assisting children's reading. A state-of-the-art speaker independent continuous speech recognizer designed for large vocabulary dictation is adapted to the task of identifying substitutions and omissions in a known text. A baseline language model for this new task is detailed and evaluated against a corpus of children reading graded passages. We ;ire able to identify words missed by a reader with an average false positive rate of 39 % ;and a corresponding false negative rate of 37 %. These preliminary results ;ire encouraging for our long-term goal of providing automated coaching for children learning to read.

Keywords: Speech recognition, language modeling, children's reading