MINISTRY OF EDUCATION AND TRAINING QUY NHON UNIVERSITY TRẦN THỊ NGỌC GIÀU EVALUATING THE QUALITY OF ENGLISH- VIETNAMESE TRANSLATIONS CARRIED OUT BY GOOGLE TRANSLATE Field: English Linguistics Code: 8.01 Supervisor: Lê Nhân Thành, Ph. BỘ GIÁO DỤC VÀ ĐÀO TẠO TRƯỜNG ĐẠI HỌC QUY NHƠN TRẦN THỊ NGỌC GIÀU ĐÁNH GIÁ CHẤT LƯỢNG CÁC BẢN DỊCH ANH-VIỆT DO GOOGLE TRANSLATE THỰC HIỆN Chuyên ngành: Ngôn Ngữ Anh Mã số: 8.01 Người hướng dẫn: TS. Lê Nhân Thành 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. Besides, I would like to express my thankfulness to all the teachers of the Department of Foreign Languages, Quy Nhon University, for their useful lessons, guidance, experience, wholehearted instruction, enthusiasm, and sympathy to make me a more knowledgeable person today. This thesis would have never been fulfilled without the assistance and support from my classmates of the 19th MA Course on the English Language at Quy Nhon University.
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 for me to complete this thesis successfully. 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 research question (1) How does Google Translate translate literary texts and technical texts in terms of translation quality? and (2) Which of these two genres does Google Translate translate better? Based on Haijar Khanmohammd and Maryam Osanloo’s (2009) conceptual framework of five common types of translation errors including orthographic errors, morphological errors, lexical errors, semantic errors, and syntactic errors, the researcher analyzed Google Translate’s Vietnamese translations of three literary texts with 5,773 words and six 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 are more closely related to culture than technical texts. Although the study achieved its aim, there were some limitations. For instance, there was no investigation on the influence of translation errors on TL readers, and the data for the study was not big enough for more reliable generalizations.
Some implications for teachers and students of translation, translators and other researchers are addressed in the thesis. iii TABLE OF CONTENTS ACKNOWLEDGEMENT. v LIST OF TABLES. vi LIST OF FIGURES.
Aim and Objectives of the Study. Scope of the Study. Significance of the Study. Organization of the Thesis.
Definition of translation. Translation quality assessment (TQA). The history of machine translation. FINDINGS AND DISCUSSION.
CONCLUSIONS AND IMPLICATIONS. Summary of the Findings. Limitations of the Study. Implications of the Study.
Implications for teachers and students of translation. Implications for translators. Implications for other researchers. 57 v ABBREVIATIONS GT Goolge translate IIMA Indian Institute of Management Ahmedabad LE Lexical errors ME Morphological errors MT Machine translation OE Orthographic errors POS Part-of-speech SE Semantic errors SL Source language SYE Syntactic errors TT Target translation vi LIST OF TABLES Table 1.
Identifiable characteristics of translation errors. Example of translation representation. Types and frequencies of errors committed by GT. The frequency of errors occurring in literary texts.
The frequency of errors occurring in the translations of the technical texts. Summary of translation errors committed by GT in the literary text and technical texts. 51 vii LIST OF FIGURES Figure 1. List of translation methods.
Types of translation shifts. Classification of translation errors. Hierarchical structure of the error typology. Three different levels of an original text and its translation.
Languages supported by GT (Google 2019). GT graphical user interface. 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 an instrument in machine translation that has been claimed by its provider to be developing at a great pace to achieve ever higher degrees of accuracy. Because GT is freely available on the Internet and has its own app on computers, tablets, and smartphones, it is accessible anywhere the Internet and Google services are available, and it easily enables users to render a text in one language into over 100 other languages with outcomes of varying quality and comprehensibility. 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 knowing how accurate its translations are.
So this study is very necessary for users to know for which genre they can easily get good results and which genre they would get less accurate results. 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 story. The first related study that has been carried out recently by Aiken and Balan (2011) is An analysis of Google Translate accuracy. The aim of the research was to compare the quality of GT’s translations and provide insights into the errors made by GT.
Aiken, Ghosh, Wee, and Vanjani (2009) have studied An evaluation of the accuracy of online translation systems in 2 communications of the IIMA. This study gave an estimate of how good a potential translation might be achieved by GT. The result of this study showed that translations between European languages were usually good, while those involving Asian languages were often relatively poor. Further, the vast majority of language combinations probably provided sufficient accuracy for reading comprehension in college.
Several studies on the use of GT in translation have focused on computational analysis. For example, Carl (2019) investigated Machine translation errors and the translation process: a study across different languages in The Journal of Specialised Translation. The findings clearly showed that expressions with MT accuracy issues into one language (English-to-Spanish) were likely to be difficult to translate also into another language for humans and for computers; whereas this did not hold for MT fluency errors. Also, Ghasemi & Hashemian (2016) conducted a study investigating A comparative study of Google Translate translations: An error analysis of English-to-Persian and Persian-to-English translations.
Its main findings were of no significant differences between the qualities of GT from English to Persian and Persian to English. Moreover, there have been a lot of master theses carried out based in the light of machine translation. Most of them have focused on the comparison of translations done by machines or translations done by machines and those done by humans in different languages. There has not been any study of the accuracy that GT could achieve in translating literary and technical texts.
This study hopes to fill in this research gap. Aim and Objectives of the Study 1. Aim This study aimed to investigate the quality of Google Translate’s translations of literary texts and technical texts from English into Vietnamese. Objectives To fulfil the above aim, the researcher: - Evaluated the quality of Google Translate’s Vietnamese translations of English literary texts and technical texts.
- Compared the quality of the translations of literary texts and that of technical texts in order to see which of these two genres Google Translate translates better. Research Questions In order to achieve the above aim and objectives, the researcher collected data and analyzed it in order to answer the following questions: 1. How does Google Translate translate literary texts and technical texts in terms of translation quality? 2. Which of these two genres does Google Translate translate better? 1.
Scope of the Study This study examined the quality of the translations carried out by Google Translate in two genres, including literary texts and technical texts. Other genres were not examined in this study. Only the quality of English – Vietnamese translations of texts of these two genres would be investigated. For each genre, the author selected 3 texts of about 4000 words in total and these texts were translated by GT.
Significance of the Study The study has both practical and theoretical significance. For theoretical aspects, the research offers insights into the quality of GT’s translations of literary texts and technical texts. Moreover, this thesis also provides knowledge about errors made by GT in its translations of literary texts and technical texts. 4 For practical aspects, the study helps students, teachers, and translators get a comprehensive overview of errors committed by GT and the occurrence of such errors in literary texts and technical texts translated by GT.
In addition, after analyzing errors committed by GT in the literary texts and technical texts, the study gives a conclusion about which genre is translated better by GT. In fact, this is a useful note for the students, teachers, and translators when using GT in their work. Organization of the Thesis The thesis was organized into five chapters. Chapter 1 (Introduction) addressed the rationale, aim and objectives, research questions, the significance of the study, the scope of the study, and the organization of the study.
Chapter 2 (Literature review) presented an overview of the translation theory, translation methods, translation shift, translation quality assessment, translation equivalence, errors in translation, machine translation, Google translation, and genres. Chapter 3 (Methods) addressed the research methods and the description of the procedures for data collection and data analysis. Chapter 4 (Findings and discussions) reported and discussed the results of data analysis. Chapter 5 (Conclusion) summarized the major findings and offered implications for practice and further studies.
THEORETICAL BACKGROUND In this chapter, the theoretical background for the present study was presented. In particular, the author focused on the definition and classification of translation and identification and translation errors of GT. Translation Theory In this section, some main contents including definition, methods, shifts, equivalence, errors of translation were described. The section was also inclusive of translation quality assessment.
Definition of translation Translation is defined in many ways and may be understood differently. Translation is one of the diverse means of communication. It sets up an association between at least two languages and their culture. Through translation, the characteristic elements from one language are transferred into another.
Translation focuses on the translator’s role, from taking a source text and turning it into one in another language, and it also concentrates on the specific product created by the translator. From the perspective of Carford (1965), translation means "the replacement of textual material in one language (SL) by equivalent textual material in another language" (p. It means that translation is the replacement of the word and grammar structures in the ST with the equivalent words and grammar structures in the TL. According to Nida and Taber (1982, p.
12) translation includes reproducing in the receptor language the closest natural equivalent of the source-language message, firstly in aspects of meaning, and secondly in aspects of style. From the explanation above, translation can be simply defined as transferring the message from the SL 6 into the TL in terms of meaning and style. Hatim and Mason (1990, p. 3), on the other hand, focus more on the communication purpose of translation saying that “translation is a communicative process which takes place within a social context.