Automatic Error Detection in the Japanese Learners' English Spoken Data

This paper describes a method of detecting grammatical and lexical errors made by Japanese learners of English and other techniques that improve the accuracy of error detection with a limited amount of training data. In this paper, we demonstrate to what extent the proposed methods hold promise by conducting experiments using our learner corpus, which contains information on learners’ errors.

• Type: Conference
• Year: 2003
• Where: ACL
• Authors: Emi Izumi, Kiyotaka Uchimoto, Toyomi Saiga, Thepchai Supnithi, Hitoshi Isahara
• Keywords: ACL 2003, ACL 2007, Japanese Learners, Lexical Errors, Methods Hold Promise