(Luận văn) evaluating the quality of english vietnamese translations carried out by google translate

MINISTRY OF EDUCATION AND TRAINING QUY NHON UNIVERSITY TRẦN THỊ NGỌC GIÀU lu an n va to ie gh tn EVALUATING THE QUALITY OF ENGLISH- p VIETNAMESE TRANSLATIONS CARRIED OUT BY w d oa nl GOOGLE TRANSLATE an lu ul nf va Field: English Linguistics oi lm Code: 8.22.02.01 z at nh z @ m co l gm Supervisor: Lê Nhân Thành, Ph.D an Lu n va ac th si BỘ GIÁO DỤC VÀ ĐÀO TẠO TRƯỜNG ĐẠI HỌC QUY NHƠN TRẦN THỊ NGỌC GIÀU lu an n va gh tn to p ie ĐÁNH GIÁ CHẤT LƯỢNG CÁC BẢN DỊCH ANH-VIỆT DO GOOGLE TRANSLATE THỰC HIỆN d oa nl w va an lu oi lm ul nf Chuyên ngành: Ngôn Ngữ Anh Mã số: 8.22.02.01 z at nh z m co l gm @ an Lu Người hướng dẫn: TS Lê Nhân Thành n va ac th si i ACKNOWLEDGEMENT I would like to thank all those who helped me complete this thesis First of all, I would like to thank my supervisor, Dr Le Nhan Thanh, who has given guidance, patience, time, support, and help essential for the completion of this thesis Without his support, this thesis would never exist lu an Besides, I would like to express my thankfulness to all the teachers of the n va Department of Foreign Languages, Quy Nhon University, for their useful lessons, tn to guidance, experience, wholehearted instruction, enthusiasm, and sympathy to make ie gh p me a more knowledgeable person today oa nl w This thesis would have never been fulfilled without the assistance and support d from my classmates of the 19th MA Course on the English Language at Quy Nhon nf va an lu University oi lm ul Last but not least, I would like to send my warmest thanks to my family and friends, whose love and encouragement were a source of inspiration and motivation z at nh for me to complete this thesis successfully z m co l gm @ an Lu n va ac th si ii ABSTRACT Google Translate may produce translations with different levels of quality depending on the kinds of text it translates This study aims to evaluate the quality of GT’s Vietnamese translations of English literary and technical texts to see which of these two genres Google Translate translates better The study tries to answer the lu an research question (1) How does Google Translate translate literary texts and n va technical texts in terms of translation quality? and (2) Which of these two genres tn to does Google Translate translate better? Based on Haijar Khanmohammd and ie gh p Maryam Osanloo’s (2009) conceptual framework of five common types of oa nl w translation errors including orthographic errors, morphological errors, lexical d errors, semantic errors, and syntactic errors, the researcher analyzed Google lu nf va an Translate’s Vietnamese translations of three literary texts with 5,773 words and six oi lm ul technical texts with 4,884 words in total The findings indicate that GT is better with the technical texts than the literary texts It is understandable as literary texts z at nh are more closely related to culture than technical texts Although the study achieved z its aim, there were some limitations For instance, there was no investigation on the gm @ influence of translation errors on TL readers, and the data for the study was not big m co l enough for more reliable generalizations Some implications for teachers and an Lu students of translation, translators and other researchers are addressed in the thesis n va ac th si iii TABLE OF CONTENTS ACKNOWLEDGEMENT .i ABSTRACTABBREVIATIONS ii ABBREVIATIONS v LIST OF TABLES vi lu LIST OF FIGURES vii an 1.1 Rationale n va CHAPTER INTRODUCTION to gh tn 1.2 Aim and Objectives of the Study 1.3 Research Questions ie p 1.4 Scope of the Study nl w 1.5 Significance of the Study d oa 1.6 Organization of the Thesis an lu CHAPTER THEORETICAL BACKGROUND 2.1 Translation Theory va ul nf 2.1.1 Definition of translation oi lm 2.1.2 Translation methods 2.1.3 Translation shifts z at nh 2.1.4 Translation equivalence 10 2.1.5 Translation errors 13 z gm @ 2.1.6 Translation quality assessment (TQA) 19 2.2 Machine Translation 22 l m co 2.2.1 The history of machine translation 22 2.2.2 Google Translate 24 an Lu 2.3 Genres 27 n va ac th si iv 2.4 Conceptual Framework 28 CHAPTER RESEARCH METHODS 30 3.1 Research Methods 30 3.2 Data Collection 31 3.3 Data Analysis 33 CHAPTER FINDINGS AND DISCUSSION 35 4.1 Literary Texts 35 4.1.1 Orthographic errors 37 lu an 4.1.2 Morphological errors 38 n va 4.1.3 Lexical errors 40 tn to 4.1.4 Semantic errors 41 4.1.5 Syntactic errors 43 gh p ie 4.2 Technical Texts 44 4.2.1 Orthographic errors 46 nl w 4.2.2 Morphological errors 46 d oa 4.2.3 Lexical errors 47 an lu 4.2.4 Semantic errors 47 va 4.2.5 Syntactic errors 49 ul nf CHAPTER CONCLUSIONS AND IMPLICATIONS 51 oi lm 5.1 Summary of the Findings 51 5.2 Limitations of the Study 54 z at nh 5.3 Implications of the Study 54 z 5.3.1 Implications for teachers and students of translation 54 @ 5.3.2 Implications for translators 55 gm l 5.3.3 Implications for other researchers 56 m co REFERENCES 57 an Lu n va ac th si v ABBREVIATIONS Goolge translate IIMA Indian Institute of Management Ahmedabad LE Lexical errors ME Morphological errors MT Machine translation OE Orthographic errors POS Part-of-speech lu GT an n va tn to SE Semantic errors Syntactic errors nl w Target translation d oa TT Source language p SYE ie gh SL oi lm ul nf va an lu z at nh z m co l gm @ an Lu n va ac th si vi LIST OF TABLES Table Identifiable characteristics of translation errors 29 Table Example of translation representation 33 Table Types and frequencies of errors committed by GT 35 Table The frequency of errors occurring in literary texts 36 Table The frequency of errors occurring in the translations of the technical texts 45 lu Table Summary of translation errors committed by GT in the literary text and an n va technical texts 51 p ie gh tn to d oa nl w oi lm ul nf va an lu z at nh z m co l gm @ an Lu n va ac th si vii LIST OF FIGURES Figure List of translation methods Figure Types of translation shifts Figure Classification of translation errors 15 Figure Hierarchical structure of the error typology 17 Figure Three different levels of an original text and its translation 20 lu Figure Languages supported by GT (Google 2019) 25 an n va Figure GT graphical user interface 26 p ie gh tn to d oa nl w oi lm ul nf va an lu z at nh z m co l gm @ an Lu n va ac th si CHAPTER INTRODUCTION 1.1 Rationale The increase in global business has provided a greater and more urgent need for quick translation An obvious tool which has been created to help meet this need is Google Translate, which is very well-known for free online machine translation Google Translate (GT) has become lu an instrument in machine translation that has been claimed by its provider to be developing at a an n va great pace to achieve ever higher degrees of accuracy Because GT is freely available on the tn to Internet and has its own app on computers, tablets, and smartphones, it is accessible anywhere the ie gh Internet and Google services are available, and it easily enables users to render a text in one p language into over 100 other languages with outcomes of varying quality and comprehensibility oa nl w Even though GT is a very popular tool used by millions of Internet users and it has improved a lot so far, it is clearly not perfect yet Therefore, we cannot rely on it blindly without d lu va an knowing how accurate its translations are So this study is very necessary for users to know for ul nf which genre they can easily get good results and which genre they would get less accurate results oi lm That would help users to decide how much trust they can put on GT when they need to translate texts that belong to different genres such as tourism news, medical information, and the short z at nh story z gm @ The first related study that has been carried out recently by Aiken and Balan (2011) is An l analysis of Google Translate accuracy The aim of the research was to compare the quality of m co GT’s translations and provide insights into the errors made by GT Aiken, Ghosh, Wee, and an Lu Vanjani (2009) have studied An evaluation of the accuracy of online translation systems in n va ac th si 44 Original text “My friends,” he said, “my friends, I-I-” But something suffocated him He could not finish the sentence (The Last Class—The Story of a Little Alsatian, p.9) Translation version Bạn bè tôi, người anh nói, người bạn tơi, tơi người khác Nhưng có nghẹt thở anh Anh khơng thể nói hết câu lu an In the above example, “My friends,” he said, “my friends, I-I-” But something suffocated n va him He could not finish the sentence” should be translated into “Các bạn tơi,” nói, to gh tn “các bạn tôi, tôi-tôi” Nhưng khiến nghẹt thở Anh khơng thể nói hết câu” p ie However, in fact, GT has not well done its functions when giving the completed different output nl w of “Bạn bè tôi, người anh nói, người bạn tơi, tơi người khác Nhưng có nghẹt thở d oa anh Anh khơng thể nói hết câu” an lu The English sentence in this example should be translated into “Các bạn tơi,” nf va nói, “các bạn tơi, tơi-tơi” Nhưng khiến nghẹt thở Anh khơng thể nói hết 4.2 Technical Texts oi lm ul câu” However, GT did not produce an accurate translation z at nh The results of the analysis of six technical texts of 4,884 words are presented in the z following table m co l gm @ an Lu n va ac th si 45 Table The frequency of errors occurring in the translations of the technical texts Type of errors Sub-types of errors Punctuation Occurrences Percentage 0% 0% Spelling 0% Morphological Verb 0% errors Noun 0.26% Extra words 0% Missing words 0.26% Semantic errors 230 59.12 Conjunction 0% Preposition 0% Article 0% 157 40.36 0% 389 100% Orthographic errors Capitalization lu an Lexical errors n va p ie gh tn to Semantic errors nl w Syntactic errors d oa Syntactic element an lu reordering Category errors ul nf va TOTAL oi lm Similar to GT’s errors in the translations of the literary texts, GT’s errors in the z at nh translations of the technical texts also consisted of five types, of which orthographic errors (inclusive of smaller types such as punctuation, capitalization and spelling), morphological errors z gm @ (consisting of wrong forms of verbs, nouns or any other part of speech), lexical errors (including m co l extra words and missing words), semantic errors, and syntactic errors (inclusive of conjunctions, prepositions, article, syntactic element reordering, and category errors) an Lu n va ac th si 46 Table 4.4 shows the distribution of the errors in GT’s translations of the technician texts Obviously, the number of errors committed in the technical texts by GT was less than half of that in the literary texts There was no error in punctuation, spelling, verbs, nouns, extra words, conjunctions, articles, and category Most of the errors were semantic and syntactic element reordering errors, with 59.12% and 40.62%, respectively There was only 0.26% of missing words 4.2.1 Orthographic errors lu an There were no errors of orthography committed by GT in translating the technical texts n va As presented in Chapter 2, orthographic errors include punctuation, capitalization, and spelling tn to This is understandable because we can use GT as a useful tool for checking the spelling gh p ie 4.2.2 Morphological errors Morphological errors consist of wrong forms of verbs, nouns or any other part of speech nl w d oa Similar to orthographic errors, there was no morphological error in verb forms when GT oi lm ul nf Original text va following sentence an lu translated the technical texts from English into Vietnamese There were only noun errors in the Ms Li said her stress led to insomnia When she did sleep, she experienced “problem- z at nh solving dreams,” which left her feeling unrested when she woke up (There’s a Stress Gap Between Men and Women Here’s Why It’s Important, p.1) z Translation version: @ gm Cô Li cho biết cô bị căng thẳng dẫn đến ngủ Khi cô ngủ, cô trải nghiệm l giấc mơ giải vấn đề, điều khiến cảm thấy không ổn định thức dậy m co Obviously, “stress” is a noun However, in the translation, “stress” is considered as an an Lu adjective The translation should be “Cô Li cho biết căng thẳng khiến cô ngủ” n va ac th si 47 4.2.3 Lexical errors Lexical errors occur when inappropriate lexical choices are made, including extra or added words and missing words In terms of lexical errors, no errors of extra words were found in GT’s translations Of 4,884 words of six technical texts, there was only one error of missing word, in particular conjunction Original text It’s not just inside the home, though Research from Nova Southeastern University found lu an that female managers were more likely than male managers to display “surface acting,” or n va forcing emotions that are not wholly felt gh tn to (There’s a Stress Gap Between Men and Women Here’s Why It’s Important, p.2) p ie Translational version nl w Nó khơng nhà Nghiên cứu từ Đại học Nova Đông Nam phát d oa nhà quản lý nữ có nhiều khả nhà quản lý nam thể diễn xuất bề mặt, hành an lu động hay ép buộc cảm xúc khơng hồn tồn cảm nhận oi lm ul 4.2.4 Semantic errors nf va In the above example, “though” was not translated by GT Semantic errors refer to cases where wrong TL words are chosen to render SL words z at nh Semantic errors were most frequently committed by GT when translating the English technical z texts into Vietnamese Let’s look at the following examples gm @ Original text solving dreams,” which left her feeling unrested when she woke up m co l Ms Li said her stress led to insomnia When she did sleep, she experienced “problem- an Lu (There’s a Stress Gap Between Men and Women Here’s Why It’s Important, p.1) n va ac th si 48 Translation version Cô Li cho biết cô bị căng thẳng dẫn đến ngủ Khi cô ngủ, cô trải nghiệm giấc mơ giải vấn đề, điều khiến cảm thấy không ổn định thức dậy The word “unrested”, in this case, is translated into “không ổn định”, which is not suitable in this context Rather, it should be translated into “không khỏe” Original text Like Ms Li, many women try to manage the added stressors to reach what Dr Joyce said lu an was an unattainable ideal “Some professional women aspire to it all: reach the top of the n va corporate ladder and fly like supermom,” she said gh tn to (There’s a Stress Gap Between Men and Women Here’s Why It’s Important, p.3) p ie Translation version nl w Giống cô Li, nhiều phụ nữ cố gắng quản lý yếu tố gây căng thẳng thêm vào để d oa đạt Tiến sĩ Joyce nói lý tưởng đạt Một số phụ nữ chuyên an lu nghiệp khao khát làm tất cả: đạt đến đỉnh cao công ty bay siêu mẫu, nói nf va The word “supermom” is a compound word including the prefix “super-” and the noun oi lm ul “mom”, not “supermodel” like GT’s translational version This sentence implies that women’s responsibility is great, both in society and in the family z at nh Original text z Nearly 170 million children worldwide, including more than 2.5 million in the United @ gm States and half a million in Britain, missed out on the first dose of the measles vaccine during the Thursday m co l past eight years, opening the door to global outbreaks of the disease, a Unicef report said on an Lu (Over 20 Million Children a Year Miss Out on First Dose of Measles Vaccine, p.1) n va ac th si 49 Translation version Gần 170 triệu trẻ em toàn giới, bao gồm 2,5 triệu trẻ em Hoa Kỳ nửa triệu trẻ em Anh, bỏ lỡ liều vắc-xin sởi tám năm qua, mở hội bùng phát dịch bệnh toàn cầu, Unicef báo cáo cho biết vào thứ năm In this context, the target language should be “theo báo cáo Unicef hôm thứ năm” 4.2.5 Syntactic errors These errors refer to errors in conjunctions, prepositions, articles, syntactic element lu an reordering, and category For the technical texts in this study, only errors of prepositions and n va syntactic element reordering were committed by GT Following are some illustrations gh tn to Original text: p ie For the annual poll, started in 2005, Gallup asks individuals about whether they have experienced a handful of positive or negative feelings the day before being interviewed nl w d oa (Americans Are Among the Most Stressed People in the World, Poll Finds, p.1) an lu Translation version: nf va Đối với thăm dò hàng năm, năm 2005, Gallup hỏi cá nhân việc họ oi lm ul trải qua số cảm xúc tích cực hay tiêu cực vào ngày trước vấn The preposition “for” should be translated into “In” (Trong) z at nh Original text z “What really stood out for the U.S is the increase in the negative experiences,” said Julie gm @ Ray, Gallup’s managing editor for world news Translation version m co l (Americans Are Among the Most Stressed People in the World, Poll Finds, p.1) an Lu n va ac th si 50 “Điều thực bật Hoa Kỳ gia tăng trải nghiệm tiêu cực”, ông cho biết, Julie Ray, biên tập viên quản lý Gallup, cho tin tức giới “Đây điều ngạc nhiên chúng tơi nhìn thấy số theo hướng này” The clause “said Julie Ray” was translated into “ông cho biết, Julie Ray” It should be “Ông Julie Ray cho biết/nói/chia sẻ” Original text “After I became a first-time mother, I quickly realized between work and family, I was so lu an busy caring for other people and work that I felt like I’d lost myself,” she said va n (There’s a Stress Gap Between Men and Women Here’s Why It’s Important, p.1) gh tn to Translation version p ie “Sau trở thành người mẹ lần đầu tiên, tơi nhanh chóng nhận cơng việc nl w gia đình, tơi q bận rộn chăm sóc người khác cơng việc tơi cảm thấy d oa đánh mình”, nói an lu The phrase “a first-time mother” means the woman giving the first birth However, GT oi lm ul làm mẹ” nf va translated it into “một người mẹ lần đầu tiên” The Vietnamese version should be “người lần đầu In short, GT’s translations of the technical texts were better than those of the literary texts z at nh For GT’s translations of the literary texts, the more frequent errors included punctuation, verbs, z nouns, semantic errors and syntactic element reordering; meanwhile, in GT’s translations of the @ m co l committed gm technical texts, semantic errors and syntactic element reordering errors were more frequently an Lu n va ac th si 51 CHAPTER CONCLUSIONS AND IMPLICATIONS In this final chapter, the researcher will summarize the main findings Also, the researcher discusses the limitations of the research as well as recommends some implications for teachers, students, translators and other researchers 5.1 Summary of the Findings Basing on the conceptual framework of the error types in translation, the researcher lu an analyzed the errors committed by GT when translating English into Vietnamese in terms of two n va genres: literary and technical texts The translation errors in the literary texts and technical texts to gh tn committed by GT are summarized in the following table: p ie Table Summary of translation errors committed by GT in the literary text and technical texts nl w Literary texts d oa Sub-types of Type of errors Occurrences 3.88% 0% 0.51% 0% 0% 0% 17.03% 0% 15.01% 0.26% 0% 0.26% oi lm errors ul Capitalization Morphological Verb 101 errors Noun 89 Extra words 0% Missing words 0.17% Semantic errors 258 43.51% z m co l gm Lexical errors z at nh Spelling Semantic errors Percentage @ Orthographic Occurrences 23 va Punctuation Percentage nf an lu errors Technical texts 230 59.12 an Lu n va ac th si 52 Literary texts Sub-types of Technical texts Type of errors Occurrences errors Percentage Occurrences Percentage 0% Conjunction 0% Preposition 23 3.88% Article 0% 0% 95 16.02% 157 40.36 0% 0% 593 100% 389 100% Syntactic errors Syntactic element reordering lu an Category errors n va TOTAL gh tn to p ie Looking at the table above, we can see that semantic errors accounted for the highest rate w (49.69%) The syntactic errors and morphological errors made up of 28.01% and 19.45%, d oa nl respectively Finally, orthographic errors and lexical errors accounted for the smallest proportions (2.65% and 0.2%, respectively) an lu nf va For orthographic errors, GT’s translations of the literary texts included 26 errors meanwhile oi lm ul its made no error in the translations of the technical errors For morphological errors, there were 190 errors in GT’s translations of the literary texts, but there was only one error in GT’s z at nh translations of the technical texts Concerning GT’s lexical errors, only one error occurred in the translations of the literary and technical texts The translations of the literary texts consisted of z @ 258 semantic errors meanwhile translations of the technical texts included 230 errors For gm technical texts had 157 errors m co l syntactic errors, the Vietnamese versions of the literary texts included 95 errors while those of the an Lu n va ac th si 53 It is concluded that GT’s translations of the technical texts are better than those of the literary texts When translating the technical texts, GT committed fewer errors than it did when translating the literary texts GT’s errors may be due to two main types of causes, namely subjective causes and objective causes Only good translators can produce translations of high quality To be able to create a good translation, the translator must be competent in both the source and target languages and have an extensive cultural background The basic reason for a poor translation is the translator’s language competence In fact, Vietnamese translators excel at lu an their own mother tongue, and their language incompetence can be considered in two broad fields n va namely vocabulary and grammatical structures However, one of the important requirements is tn to the cultural background because, without cultural background, literary translation cannot achieve gh p ie good quality Therefore, translators need to pay attention to their own culture and the culture of the foreign language that they work with nl w d oa The objective cause is the fact that Vietnamese and English have many differences in an lu vocabulary and grammatical rules, which can cause difficulties for translators to obtain good nf va translations Moreover, translation, especially literary translation, is not simply a linguistic oi lm ul transformation of texts Rather, it is a rendering of cultural concepts from one language to another Cultural differences can make difficulties for translators Asian culture in general and z at nh Vietnamese culture in particular have many things uncommon in Western and American culture z Various concepts that are familiar to Vietnamese people may be alien to English-speaking @ gm readers Translators will find it difficult to choose equivalents To have a successful translation of own culture and the culture of the foreign language m co l high quality, translators have to overcome the obstacles created by the difference between their an Lu n va ac th si 54 Although GT has not proved to be a very good machine translator, we cannot deny its advantages In other words, it can be said that GT's translation quality is quite good for those who not speak a certain language to understand the meaning of a website, for example, written in English We cannot ask for GT’s higher translation quality even though Google is committed to continually improving and upgrading GT’s translation quality because GT is a just "machine that knows how to translate" and not "a flesh and blood interpreter" (Pym, 1992, p.281) Indeed, this "translation machine" still uses the "word-for-word" translation mechanism that directly lu an compares the original words with the equivalent words in the target language and then translates n va it into the TL Also, there are quite many grammatical sentence patterns that are present in the GT tn to database, but they are not always properly and appropriately used gh p ie 5.2 Limitations of the Study Although the study achieved its aim, there are some limitations Firstly, due to the limited nl w d oa time, the author did not investigate the influence of translation errors on TL readers Second, the an lu analysis was limited to more than 10,000 words of the texts cited from two genres, so the errors nf va found in this study and their frequency may not apply to GT’s translations of texts in other oi lm ul genres Additionally, the data was not big enough to offer the most comprehensive and exact overview of the quality of the English-Vietnamese translations carried out by GT z at nh 5.3 Implications of the Study z In this section, the researcher pressents the impilications for teachers, students, and 5.3.1 Implications for teachers and students of translation m co l gm @ translators and for other researchers This study examined the errors committed by GT when it translated the literary and an Lu technical texts written in English to Vietnamese Firstly, the results of the study can be used as a n va ac th si 55 guideline for teachers to recognize the errors made by GT as well as students These errors include errors in punctuation, spelling, verbs, nouns, extra words, missing words, semantic errors, conjunctions, articles, syntactic element reordering, and category errors Secondly, the results indicate the strengths and weaknesses of GT in translating texts of different genres The results of the study suggest that the GT had more difficulties in translating the literary texts compared with the difficulties it met in translating the technical texts These findings are beneficial to teachers in that they should ask their students who use GT to pay more attention to GT’s translations of lu an literary texts Finally, the school or authority can use these results to design the curriculum in n va order to enhance their English competence as well as set an appropriate and supportive tn to environment for their language learning In particular, English semantics and collocations should gh p ie be taught The students should be more exposed to the English culture by speaking with native speakers and studying authentic English texts, for instance nl w d oa 5.3.2 Implications for translators an lu GT, like other automatic translation tools, has its limitations GT may be able to help nf va people understand the general content of foreign language texts, but it does not always deliver oi lm ul correct translations Translators should use GT only as a reference, especially when translating contracts, agreements, technical texts or other official and legal documents Thus, total reliance z at nh on GT is unwise for translators z The results of this study show that there are quite many errors if users use GT for their @ gm translation In other words, using GT does not lead to perfect translations of the original texts m co l The results indicate that GT may be better used for technical texts than literary ones Thus, translators must be aware of potential complications such as words with multiple meanings, an Lu n va ac th si 56 words that have specific notions in specific contexts, words that are not recognized by GT, words that have different levels of formality, etc 5.3.3 Implications for other researchers In the process of Vietnam’s integration into the world economy and culture, English– Vietnamese translations become more and more significant when acting as a bridge connecting different cultures This progress also requires translations of high quality, in particular from English to Vietnamese and vice versa lu an Based on the results and the limitations of the study, some suggestions for further n va research are as follows gh tn to Firstly, the results of this study cannot be generalized to all genres Therefore, it is p ie proposed that future studies will be carried out using texts of other genres Additionally, the length of each English text should be longer to ensure more objective generalizations about the nl w d oa quality of GT’s translations in terms of genres an lu Secondly, this study examined the quality of GT’s translations of English texts into nf va Vietnamese Further studies should investigate GT’s translations of Vietnamese texts into English oi lm ul texts Perhaps, the results of such studies will be very different from the results of the present study owing to the linguistic differences in these languages z at nh It can be concluded that GT accelerates translation, and it may help translators produce z faster and even better translations However, as the results of the study indicate, GT gave better @ gm translations of technical texts compared to those of literary texts Therefore, translators should quality m co l pay more attention to errors often committed by GT so that their translations will get better an Lu n va ac th si 57 REFERENCES Amin Karimnia (2011) Waddington’s model of translation quality assessment: A critical inquiry Tehran: Islamic Azad University Berelson, B (1952) Content analysis in communication research Glencoe, IL: Free Press Cabeceran, F., M., R C.J., M., M A., J B, & Rodríguez Fonollosa, J A (2010) Linguistic-based evaluation criteria to identify statistical machine translation lu an errors The 14th annual conference of the European association for machine va translation Saint-Raphaël n tn to Catford, J C (1965) A linguistic theory of translation Oxford: Oxford University Press gh Farah Hana Amanah (2017) Errors made by Google Translate and its rectification by p ie human translators Menara: University of Malaysia w Haijar Khanmohammd & Maryam Osanloo (2009) Moving toward objective scoring: A oa nl rubric for translation assessment JELS, 1(1), 131-153 d Hatim, B., & Mason, I (1990) Discourse and the translator London: Longman lu an Holsti, O R (1968) Content analysis In G L E A (Eds.) (Ed.), The handbook of social nf va psychology, (2), 596-692 oi lm ul House, J (1997) Translation quality assessment: A model revisited Tübingen: Narr Kerlinger, F N (1986) Foundations of behavioral research, 3, New York: Holt, z at nh Rinehart, and Winston Krippendorff, K (1980) Content analysis: An introduction to its methodology London: z Sage Publications @ gm Mechmood, A., Amber, R., Ameer, S., & Faiz, R (2014) Transitivity analysis: research in social sciences, 2(4) m co l Representation of love in Wilde's the nightingale and the rose European journal of an Lu n va ac th si 58 Mossop, B (1989) The objective and cultural norm of translation L’erreur en traduction, 2, 55-70 Munday, J (2008) Introducing translation studies London: Routledge Newmark, P (1980) Approaches to translation Oxford: Pergamon Press Newmark, P (1985) About translation Borisova: Multilingual Matters Newmark, P (1988) A textbook of translation New York: Prentice-Hall Newmark, P (1995) A textbook of translation New York: Prentice-Hall Nida, E A (1964) Toward a science of translation Leiden: E J Brill lu an Nida, E A., & Taber, C R (1982) The theory and practice of translation Leiden: E.J n va Brill Nord, C (1997) Translating as a purposeful activity Manchester: St Jerome Publishing to gh tn Popovic, A (1976) A dictionary for the analysis of literary translation Edmonton: p ie University of Alberta Pym, A (1992) Translation error analysis and the interface with language teaching In C Benjamins d oa nl w D A L (Eds.) (Ed.) The teaching of translation, 279-288 Amsterdam: John an lu Radford, A (1997) Syntactic theory and the structure of English: A minimalist approach Cambridge: Cambridge University Press va ul nf Taylor, S., Bogdan, R., & DeVault, M (1998) Introduction to qualitative research Trosborg, A (1997) Text oi lm methods: A guidebook and resource (3rd ed.) New York: Wiley typology: Register, genre and text type z at nh Amsterdam/Philadelphia: John Benjamins Publishing Company Vinay, J P., & Darbelnet, J (1995) A methodology for translation London: Routledge z m co l gm @ an Lu n va ac th si