An Investigation Into C-E Translation Skills Of Serial Verb Constructions In Criminal Judgments: A Corpus-based Approach

This dissertation is an investigation-based analysis of the English translation ofSerial Verb Constructions (hereinafter referred to as “SVC1” or “SVCs” as the casemay be) in Chinese criminal judgments. SVC is a cluster of verbs expressing a seriesof complicated actions and/or thoughts in a single sentence. This sentential structureis especially prominent in criminal judgments and is often employed by defendants orwitnesses to describe complicated actions, excuse themselves or shun responsibilities.It is a unique linguistic construction found only in west-African regions andEast-Asian language families, and is grammatically absent and unacceptable in theEnglish language. Hence, how to translate this complicated element into Englishposes special challenges for translators.The present thesis aims to explore and discover the types and subtypes oftranslation skills and regularities employed in the English translations of the SVCs inChinese criminal judgments by identifying and sorting out both the distribution ofSVCs in Chinese criminal judgments and their corresponding translation skills in thetarget language.To achieve this general goal, a theoretical framework on the basis of a review ofthe most relevant literature is constructed so as to guide the research process andensure homogeneity in concepts and methods which are utilized in data collectionand analysis. A parallel corpus comprising3254SVCs segments and a correspondingnumber of their English translations in25Chinese criminal judgments and theirEnglish translations (corpus size:100,000Chinese characters and80,000Englishwords), all cited from the Chinalawinfo’s criminal judgment translation databank, isconstructed. The said corpus provides abundant resources for both qualitativeexploration and relatively quantitative analysis of SVCs. Both the SVCs in Chinese criminal judgments and their English translation skills are tagged by following theframework proposed to guarantee the consistency and objectivity of the datacollected for the present research. Corpus software programs such as CUC ParaConc,AntConc and EditPlus are utilized to extract both types of data and their respectivesubtypes. These programs also facilitate the procedure of data analysis.Following description and analysis of such data and their corresponding subtypes,it is found that SVCs indicating temporal relation and interactional relation (T1ST1and T1ST3) play dominant roles. Specifically, SVCs where two or more eventshappen at the same time outweigh the other semantic categories (T1ST1-SIMUL). Torender SVCs into English, translators are inclined to draw support from nine majortranslation skills from textual and grammatical levels, all of which are unevenlydistributed in the corpus. It is also found that each SVC subtype has its ownpreference towards certain translation skills according to frequency comparison. Onesurprising finding of this research is that the types of SVC translation skills incriminal judgments exhibit no significant difference from those in general-purposetexts based on comparison with previous available academic findings.Despite the relatively small scale of the corpus, the present study piles up effort intheoretical enrichment of SVCs and their English translation skills. It also shedslights on the practice of legal translation, improvement of translation efficiency andmaturation of machine translation.