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Use of speech technologies in the classroom is often limited by the inferior acoustic conditions as well as other factors that might affect the quality of the recordings. We describe MyTurnToRead, an e-book-based app designed to support an interleaved listening and reading experience, where the child takes turns reading aloud with a virtual partner. The child’s reading turns are recorded, and processed by an automated speech analysis system in order to provide feedback or track improvement in reading skill. We describe the architecture of the speech processing back-end and evaluate system performance on the data collected in several summer camps where children used the app on consumer-grade devices as part of the camp programming. We show that while the quality of the audio recordings varies greatly, our estimates of student oral reading fluency are very good: for example, the correlation between ASR-based and transcription-based estimates of reading fluency at the speaker level is r=0.93. These are also highly correlated with an external measure of reading comprehension.