Chinese-English Translation Of Medical Texts: Errors And Strategies

The past several decades have seen tremendous advances in ESP (English for Specific Purposes) translation. In the field of medicine, the perpetual expansion of science and technology necessitates unprecedented worldwide academic cooperation and communication. To follow the latest trend, many scholars have concentrated their efforts on research into translation of English for Medical Purposes (EMP), an integral part of ESP translation. Poor medical translation hinders mutual understanding and the diffusion of scientific knowledge. Error analysis (EA), a branch of applied linguistics and an approach to the analysis of language acquisition, undoubtedly has made great contributions to second language (L2) teaching and learning. Remarkable achievements in this field have not only extended the boundaries of studies on EA but also broadened the scope of medical translation research. Although most previous EA-related researches have been concentrated on EFL (English as a foreign language) learners'writing, speaking, and recently Chinese-English (C-E) translation of public signs, only limited literature has been available on error analysis of C-E translation of medical texts based on an integration of statistical data and exemplifications.Under the guidance of Carl James'error categorization framework and Eugene Nida's translation theory of functional equivalence, the present research project was intended to identify, classify, describe, and diagnose the common errors in C-E translation of medical texts made by many first-year Chinese graduate students at a medical university. More importantly, we have attempted to provide some strategies for error-correction and functional equivalence of medical translation by investigating a corpus from a range of authentic sources.To attest the feasibility of the present study, a pretest was first conducted in a mini-sized corpus, including 50 medical texts translated from Chinese into English by 25 participants. Then, 164 first-year graduate students were randomly selected as participants using cluster sampling at the Fourth Military Medical University (FMMU) to establish a translation corpus. In combination with quantitative and qualitative analyses, 200 samples chosen from the corpus at random were investigated in terms of linguistic errors and error causes by Carl James'error classification (2001). The classified errors were computed with Microsoft Office Excel 2003. Block design analysis of variance (ANOVA) and least significant difference t test (LSD-t) were performed with SPSS16.0 software for exploring error distribution, frequency and regularity at different levels of language.The major findings of our study were as follows:1) A total number of 1451 errors were detected in the 200 sample translations, of which text errors (1259, 86.77%) took the lead, followed by discourse errors (132, 9.10%) and substance errors (60, 4.13%). Significant differences were found between the three different levels in the frequency of errors (P<0.05).2) As for text errors, grammar errors (384, 30.50%) were heavily outnumbered by lexical errors (875, 69.50%), with a statistically significant difference between them (P<0.05).3) In lexical errors, as compared with verbosity (248, 28.34%) and formal errors (237, 27.09%), semantic errors (390, 44.57%), including confusion of sense relations and collocational errors, ranked first (P<0.05) but no marked difference was observed between verbosity and formal errors (P>0.05). Syntax errors constituted the majority of grammar errors. There was a significant difference between syntax errors (294, 76.56%) and morphology errors (90, 23.44%) in frequency (P<0.05).4) Intralingual errors, which accounted for approximately 58.10 percent of the total, were much more frequent than interlingual (585, 40.31%) and receptive errors (23, 1.59%) (P<0.05).We can draw the following conclusions from our study:1) Some Chinese EFL learners at intermediate or even advanced level still make an overwhelming number of errors in spelling, punctuation, word choice, grammar, and coherence due to their deficiencies in linguistic competence and bilingual communication. Therefore, more attention should be paid to the cultivation of the learners'language competence.2) Lexis and grammar are two crucial factors in C-E medical translation. They present big challenges to EFL learners. It is very important for teachers to help students better understand lexical semantic relations and collocation as well as syntactical rules.3) The identified sources of errors in C-E medical translation are mainly from the intrinsic complexity of English and some Chinese learners'attempts to make false hypotheses about English rules from their limited experience. Our finding is consistent with the previous studies by Barry Taylor (1975), Wang Tongfu (1984) and other scholars. The key to successful translation lies in a good mastery of the English language and the typical features of medical English.4) Although the occurrence of interlingual errors is relatively low, negative transfer from the source language (SL) to the target one remains a major barrier for Chinese learners of English. They should try to understand the differences between Chinese and English languages and avoid mother-tongue interference in English learning and translation.For the first time we have carried out a corpus-based study on medical texts by combining error analysis and translation theory of functional equivalence. The corpus-based error analysis will help Chinese learners, especially medical workers identify the common errors in C-E medical translation and improve their competence in translation. Besides, the analysis and strategies proposed in our study could be used by teachers of medical English to improve their teaching and translators to produce quality translation.