This work targets building an oral reading “tutor” that provides automatic and reliable feedback to children learning to read. The work uses state-of-the-art in speech recognition technology coupled with prosody modeling. The system is tested on available datasets of children’s readings in English as second language. The expected challenges relate to dealing with children’s speech demonstrating a variety of skill levels. Both word decoding accuracies and prosody attributes like phrasing and prominence are considered for assessment. The relation between different acoustic features computed from the speech signal and the perceived quality will be investigated. The goal is to have a system that can provide feedback and evaluation that is highly correlated with that of human judges such as language teachers.