Automated Assessment of Oral Reading Prosody

Authors:
Jack Mostow;Minh Duong
Affiliations:
Project LISTEN, Carnegie Mellon University, Pittsburgh, PA, USA;Project LISTEN, Carnegie Mellon University, Pittsburgh, PA, USA
Venue:
Proceedings of the 2009 conference on Artificial Intelligence in Education: Building Learning Systems that Care: From Knowledge Representation to Affective Modelling
Year:
2009

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Abstract

We describe an automated method to assess the expressiveness of children's oral reading by measuring how well its prosodic contours correlate in pitch, intensity, pauses, and word reading times with adult narrations of the same sentences. We evaluate the method directly against a common rubric used to assess fluency by hand. We also compare it against manual and automated baselines by its ability to predict fluency and comprehension test scores and gains of 55 children ages 7--10 who used Project LISTEN's Reading Tutor. It outperforms the human-scored rubric, predicts gains, and could help teachers identify which students are making adequate progress.