Paper: Automatic Assessment of the Speech of Young English Learners

ACL ID W14-1802
Title Automatic Assessment of the Speech of Young English Learners
Venue Innovative Use of NLP for Building Educational Applications
Session
Year 2014
Authors

This paper introduces some of the research behind automatic scoring of the speak- ing part of the Arizona English Language Learner Assessment, a large-scale test now operational for students in Arizona. Ap- proximately 70% of the students tested are in the range 4-11 years old. We cover the methods used to assess spoken responses automatically, considering both what the student says and the way in which the stu- dent speaks. We also provide evidence for the validity of machine scores. The assessments include 10 open-ended item types. For 9 of the 10 open item types, machine scoring performed at a similar level or better than human scoring at the item-type level. At the participant level, correlation coefficients between machine overall scores and average human overall scores were: Kinderga...