基于汉英语料库(PACCEL-S)的口译高频时态错误分析

摘    要

时态错误在中国英语学习者所犯错误中占不可忽视的比例，围绕其展开的研究也成为应用语言学研究的热点之一,并且涌现出了大批围绕时态错误研究的论文和专著。对英语学习者来说，选用正确的时态可以使他对英语的应用更纯正地道，更接近英语为母语者的水平。中英文在时态方面的差别加大了英语专业学生汉英口译的难度。
语料库语言学兴起以后，大量基于语料库的时态研究随之涌现。在英语时态研究领域，基于语料库的研究方法已经成为一种新的研究模式。这种研究方法基于大量的语言真实资料，从调查语言信息分布的规律着手研究语言在现实中使用的规律和模式。
大批学者对时态所呈现出的特点和用法进行了更加深入全面的探讨,而对时态错误分析的研究较少。论文以中国大学生英汉汉英口译语料库(PACCEL-S)为基础，以英语专业大学生作为研究对象，找出中国英语学习者汉英口译中的高频时态错误，依据错误标注及借助语料库检索软件和统计软件，对学习者汉英口译中的时态错误进行了定量和定性分析，旨在发现学习者时态错误的一些特点,并找出这些错误产生的来源 ,以期给英语时态教学提供一些启示。

关键词： 时态； 时态错误； 语料库； 语料库研究方法； 错误分析
Abstract

Tense error occupies a noticeable proportion among the errors committed by English majors in China. The researches around the tense error have become one of the hot spot of applied linguistics. Papers and monographs about the tense error have emerged in large numbers. To English learners, choose the correct tense can make them apply English more authentic and closer to the level of English native speakers. The great difference on the aspect of tense between English and Chinese makes it very difficult for English majors to do Chinese-English interpretation.
After the rise of corpus linguistics, corpus-based researches began to come out. A corpus-based approach has becoming a new research mode in the field of English tense research. It is empirical, analyzing the actual patterns of use in natural tests. It utilizes a large and principled collection of natural tests as the basis for analysis.
Many scholars probed deeply the feature and usage of tense, while they analyzed little about the tense error. Based on the Parallel Corpus of Chinese EFL Learners-Spoken (PACCEL-S), the paper regards the English majors as the research subject and searches out the high-frequency tense error committed by English majors in the process of Chinese-English interpretation. With the error tag and the relative software, the paper makes qualitative and quantitative analysis of the tense error and aims at finding the characters and source of tense error committed by English majors

Key Words:  tense;  tense error;  corpus;  corpus-based approach;  error analysis

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