Advances in children's speech recognition with application to interactive literacy tutors
Advances in children's speech recognition with application to interactive literacy tutors
Automatic scoring of children's read-aloud text passages and word lists
EdAppsNLP '09 Proceedings of the Fourth Workshop on Innovative Use of NLP for Building Educational Applications
Advances in children's speech recognition within an interactive literacy tutor
HLT-NAACL-Short '04 Proceedings of HLT-NAACL 2004: Short Papers
Automated Assessment of Oral Reading Prosody
Proceedings of the 2009 conference on Artificial Intelligence in Education: Building Learning Systems that Care: From Knowledge Representation to Affective Modelling
AAAI'97/IAAI'97 Proceedings of the fourteenth national conference on artificial intelligence and ninth conference on Innovative applications of artificial intelligence
My science tutor: A conversational multimedia virtual tutor for elementary school science
ACM Transactions on Speech and Language Processing (TSLP)
Automatic assessment of expressive oral reading
Speech Communication
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We present initial results of FLORA, an accessible computer program that uses speech recognition to provide an accurate measure of children's oral reading ability. FLORA presents grade-level text passages to children, who read the passages out loud, and computes the number of words correct per minute (WCPM), a standard measure of oral reading fluency. We describe the main components of the FLORA program, including the system architecture and the speech recognition subsystems. We compare results of FLORA to human scoring on 783 recordings of grade level text passages read aloud by first through fourth grade students in classroom settings. On average, FLORA WCPM scores were within 3 to 4 words of human scorers across students in different grade levels and schools.