Development of an Automatic Evaluation System of Reading-Aloud and Shadowing Performances by Japanese EFL Learners Using the Latest Speech Technology

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Although shadowing is considered to be effective in improving EFL learners’ listening and speaking skills, it is both difficult and time consuming to assess shadowing performance. To solve this problem, an automatic assessing system has been newly developed using the latest speech information technology: GOP (Goodness of Pronunciation). The computer automatically compares the learner’s shadowed speech with an acous tic model based on the original text on a phoneme basis and computes numerical scores which indicate how close the learner’s shadowed speech is to the original. To confirm the validity of this automatic assessment, an experiment was conducted. Japanese EFL learners with proficiency levels ranging from 200s to 900s measured by TOEIC scores were requested to record their shadowing into the computer while listening to passages, which had been never presented before, read by a native speaker of English at a speed of approximately 140 words per minute. Then the scores obtained by the automatic system were compared to those rated manually by veteran EFL instructors. A high correlation (r=0.85) was observed between the two; thus this system is significantly valid and also saves much time and energy in assessing shadowing performance. Since the automatic scores of the learners were also highly correlated with their TOEIC scores (r=0.82), the shadowing performance can predict their overall proficiency scores. Based on the regression model, this system can predict and present TOEIC score levels. Therefore this automatic assessing system enables EFL learners to understand objectively how well they have conducted shadowing and also grasp their own proficiency levels.