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Automatic Measuring of English Language Proficiency for Global Communications

全球交流英语语言能力自动测量

基本信息

批准号：
16300048
负责人：
YAMAMOTO Seiichi
金额：
$ 9.38万
依托单位：
Doshisha University (2005-2007)Advanced Telecommunications Research Institute International (2004)
依托单位国家：
日本
项目类别：
Grant-in-Aid for Scientific Research (B)
财政年份：
2004
资助国家：
日本
起止时间：
2004 至 2007
项目状态：
已结题

来源：
https://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-16300048/
关键词：
e-Learning TOEIC translatability English corpus learner corpus fill-in-the-blank question measuring of translation quality measuring of proficiency 学習者コーパス

项目摘要

Purposes of this re arch are (1) creation of a learner corpus which contains English sentences translated by various Japanese subjects of different English proficiency and some additional items available for subjective and objective evaluation of translation quality, and (2) development of an automatic measuring method of English proficiency. Main research results are as follows ;1. As tools for automatic measuring English proficiency, we created a learner corpus of 150,000 English sentences translated by 500 Japanese subjects, of which Japanese source sentences were randomly selected from BTEC (Basic Travel Expression Corpus), English-Japanese parallel corpus of 500,000 paired sentences, and textbooks on English for junior and senior high schools. Ten reference sentences per each source sentence were made to measure some features such as edit-distance, similarity of n-grams between the reference sentences and translated sentences by the subject. Qualities of some of translated sentenc … More es in the learner corpus were subjectively evaluated by native English speakers who are frequent speaker of Japanese.2. Correlation were calculated between subjective evaluation by the English native speakers and objective evaluation such as BLEU for some English sentences translated by the subjects, and high correlation was assured if dozens of English sentences were utilized. This experimental result assured that the objective evaluation method of BLEU, which was proposed to objectively evaluate quality of sentences translated with MT technologies, can be used for measuring English proficiency of the subjects.3. Different method for selecting target sentences for translation were checked necessary number of target sentences in order to obtain a high correlation score, and one selection method for obtaining high correlation with smaller number sentences was proposed.4. The learner corpus is expected to be used for various applications besides automatic measuring of English proficiency. One of the other applications is to create a probabilistic language model which represents lexical and syntactical difference between utterances by native English speakers and Japanese. In order to verify the idea, we created a probabilistic language model such bi-gram and tri-gram and linearly interpolated them with a language models which were trained with BTEC corpus, a large text corpus of canonical English sentences. The experimental results using the linearly interpolated language model shown that the language model provided better word accuracy than a language model trained with BTEC alone. This shows that the language model adaptation between a model trained with the learner corpus and a model trained with large corpus of native English is effective for compensating for the mismatch between the lexical and syntactical characteristics of native speakers and second language speakers. Less

本研究的目的是：（1）建立一个包含不同英语水平的日本人翻译的英语句子的学习者语料库，以及一些可用于主观和客观评价翻译质量的附加项目;（2）开发一种英语水平的自动测量方法。主要研究成果如下：1.作为自动测量英语水平的工具，我们创建了一个由500名日语受试者翻译的15万个英语句子的学习者语料库，其中日语源句是从BTEC（基本旅行表达语料库）、50万个成对句子的英日平行语料库以及初中和高中英语教科书中随机选择的。每个源句制作10个参考句，以测量一些特征，如编辑距离，参考句和翻译句子之间的n-gram相似度。某些翻译作品的质量c ...更多信息学习者语料库中的词是由经常说日语的英语母语者主观评价的.对被试翻译的英语句子进行相关性分析，结果表明，英语母语者的主观评价与客观评价（如BLEU）之间存在相关性，如果使用几十个英语句子，则相关性较高。实验结果表明，BLEU客观评价方法能够客观地评价机器翻译句子的质量，可以用于测量受试者的英语水平.不同的选择翻译目标句的方法，检查必要数量的目标句，以获得高的相关性得分，并提出了一种选择方法，以获得高的相关性与较少的句子数量.除了自动测量英语水平外，学习者语料库还有望用于各种应用。另一个应用是创建一个概率语言模型，它代表母语为英语的人和日语的话语之间的词汇和句法差异。为了验证这一想法，我们创建了一个概率语言模型，如二元和三元，并线性插值与语言模型，训练与BTEC语料库，一个大的文本语料库的规范英语句子。使用线性插值语言模型的实验结果表明，该语言模型提供了更好的词的准确性比单独用BTEC训练的语言模型。这表明，用学习者语料库训练的模型和用母语英语的大语料库训练的模型之间的语言模型适配对于补偿母语者和第二语言说话者的词汇和句法特征之间的失配是有效的。少