Computer Assisted Language Learning system based on dynamic question generation and error prediction for automatic speech recognition

Abstract

We have developed a new Computer Assisted Language Learning (CALL) system to aid students learning Japanese as a second language. The system offers students the chance to practice elementary Japanese by creating their own sentences based on visual prompts, before receiving feedback on their mistakes. It is designed to detect lexical and grammatical errors in the input sentence as well as pronunciation errors in the speech input. Questions are dynamically generated along with sentence patterns of the lesson point, to realize variety and flexibility of the lesson. Students can give their answers with either text input or speech input. To enhance speech recognition performance, a decision tree-based method is incorporated to predict possible errors made by non-native speakers for each generated sentence on the fly. Trials of the system were conducted by foreign university students, and positive feedback was reported.