本研究运用语料库语言学的方法， 以大学英语英汉翻译测试的译文语料及其正式人工评分为研究对象， 通过语料标注和统计分析， 揭示翻译测试人工评分中评分员关注的主要因素， 并运用多元线性回归方法自动构建评估模型加以验证， 其评价结果与人工评分的皮尔森相关系数达到0.78. 本文以实证的方法初 步揭示大学英语翻译测试人工评分中评分员关注的反映译文质量的文本特征项， 为英汉翻译测试译文的自 动量化评价研究提供一些有益的参考 。

In this research the E-C translations from a self-built corpus of College English Competence Test were first manually annotated with translation errors according to potential evaluative parameters ，then the translation errors were concordanced in the light of each potential evaluative parameter and statistically ana- lyzed for correlations with the E-C translations ’formal manual scorings respectively． Thus some statistically significant evaluative parameters that are actually functioning in E-C translation manual scorings were tentative- ly identified ，and verified by an automatically constructed evaluation model of multiple linear regression ， whose evaluation performances bear a Pearson correlation of 0 ． 78 with the formal manual scorings． So it can be concluded that the study tentatively reveals the translations ’text features that raters have been paying close attention to in current E-C translation scoring practice for college English testing from an empirical perspec- tive ，and it might as well shed some light on automatic quantitative evaluation of E-C translations in language testing．