Oral Reading Fluency Assessment By Voice Processing
Date Issued
2009
Date
2009
Author(s)
Lu, Po-Hsuan
Abstract
The study investigates a signal processing technique for the assessment of oral reading fluency to assist children’s reading achievement. Reading voices recognition based on a Hidden Markov Model and the Mandarin Chinese syntax is used to improve the real time character recognition rate out of children’s reading voices. Fluency assessments were performed for reading speed, word accuracy, and prosody. Accuracy was estimated by a voice recognition system. Reading speed is defined as the number of characters read per minute. Prosody includes three parts: pause duration, pitch, and stress. Experiments were conducted to demonstrate the oral reading fluency measures derived from reading sounds of children with different fluency levels. Feedback instructions or indexes could be generated out of the oral reading fluency measures to children for improving their reading achievement.
Subjects
oral reading
fluency
assessment
Mandarin syntax
hidden Markov model
Type
thesis
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