A Special Parser for Learning English Composition-Error Analysis & Learners Model for ILTS

摘要：

By embedding the function of automatically correcting nearly free format English translations of given Japanese sentences, we have developed a new ILTS(intelligent language tutoring system) for improving English Writing Skills in a L2 tutoring environment. In addition to a diagnostic engine capable of identifying grammatical, lexical and word usage errors of students input translations and returning error contingent feedback, we have developed a simple table lookup parser for displying the grammar trees. The table look-up parser parses a user input, which is always erronous, by simply matching the extended part-of-speech tag sequence of a closing sentence in a template of ILTS to the entries of a look-up-table, in which each extended part-of-speech tag array corresponds to one grammar tree. The complexity of the table lookup parser is O(n), where n denotes the length of a sentence. This shows a marked improvement over the general purpose parser of which the complexity is O(n3).

关键词： intelligent language learning system machine learning machine translation natural language processing

作者: Liang Chen Naoyuki Tokuda

作者单位: Computer Science Department, University of Northern British Columbia, Prince George, BC V2N 4Z, Cana R&D Center, SunFlare Company, Tokyo, Japan

会议类型: 国际会议

会议名称: 2009 International Conference on Machine Learning and Cybernetics(2009机器学习与控制论国际会议)

会议地点: 保定

会议语种:英文

页码: 3696-3700

在线出版日期: 2009-07-12（万方平台首次上网日期，不代表论文的发表时间）