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CHAPTER FIVE CONCLUSION, FINDINGS, and RECOMMENDATIOINS 5.1 Introduction 49 5.2 Conclusion 49 5.3 Findings: 49 5.3 Recommendations: 50 References: 51 Appendixes 53

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CHAPTER FIVE CONCLUSION, FINDINGS, and RECOMMENDATIOINS 5.1 Introduction 49 5.2 Conclusion 49 5.3 Findings: 49 5.3 Recommendations: 50 References: 51 Appendixes 53 Developing EFL learners Awareness about Machine Translation Problems (A case Study of Gezira University Students , Faculties of Education Hasaheisa, Sudan, 2014) Mohamed Adam Farajallah Kuku Submitted in Partial Fulfillment of the Requirements for the Degree of Master of Arts in English Language Teaching (ELT) Department of Foreign Languages Faculty of Education, Hasaheisa University of Gezira 5102 1 Developing EFL learners Awareness About Machine Translation Problems (A case Study of Gezira University Students , Faculties of Education Hasaheisa, Sudan, 2014) Mohamed Adam Farajallah Kuku Supervision Committee Name Position Signature 1- Dr. Mubarak Siddique Main Supervisor …………… 2- Dr. Ahmed Gasmal Seed Co- Supervisor …………… 2015 2 Developing EFL learners Awareness About Machine Translation Problems (A case Study of Gezira University Students , Faculties of Education Hasaheisa, Sudan, 2014) Mohamed Adam Farajallah Kuku Examination Committee Name Position Signature 1- Dr. Mubarak Siddig chairperson 2- Dr. external examiner 3- Dr. internal examiner Date of examination / /2015 3 Table of contents Subject Page CHAPTER ONE INTRODUCTION 1.0 Background 1 1.1 Statement of the problem 2 1.2 Objectives of the study 2 1.3 Questions of the study 2 1.4 Hypotheses of the study 2 1.5 Significance of the study 3 1.6 Methodology 3 1.7 Limitations of the study 3 CHAPTER TWO LITERATURE REVIEW 2.0 Introduction 4 2.1 Definition 4 2.1.1 The term and the concept of "translation" 4 2.1.2 Common misconceptions 5 2.3: History of Translation 6 2.4 Translation and Interpretation: 7 2.5 Translation process 8 2. 5.1measuring success in translation 9 2.5 Specialized types of translation 11 2.5.1 Administrative translation 11 2.5.2 Commercial translation 11 2.5.3 Computer translation 12 2.5.4 General translation 12 2.4.5 Legal translation 12 2.5.6 Literary translation 12 2.5.7Medical translation 14 2.5.8 Pedagogical translation 14 4 2.5.9 Scientific translation 15 2.5.10 Scholarly translation 15 2.5.11 Technical translation 15 2.5.12 Translation for dubbing and film subtitles 15 2.5.13 Translation of religious texts 16 2.5.14 Machine translation 17 2.5.14.1 Computer-assisted translation 17 2.5.15 Cultural translation 18 2.6 : 2.6 Machine translation 19 translator supports the machine. 19 2.6.1 Computer-assisted translation 19 2.7 Translation problems 21 2.7.1 General problems 21 2.7.2 The problem of "untranslatability" 22 2.5.16 Criticism of Machine Translation 24 Machine Translation Strategies 28 CHAPTER THREE METHODOLOGY 3.0 Introduction 34 3.1 Sampling 34 3.3 Tools for collecting Data 34 3.3.1 Contents of the Questionnaire 34 3.3.1.1 Validity of the Questionnaire 34 3.3.1.2 Reliability of the Questionnaire 35 3.4 Instrument for Data Analysis 36 5 CHAPTER FOUR DATA PRESENTATION AND ANALYSIS 4. 0 Introduction 37 4.1Data analysis and Dissection 37 CHAPTER FIVE CONCLUSION, FINDINGS, AND RECOMMENDATIOINS 5.1 Introduction 49 5.2 Conclusion 49 5.3 Findings: 49 5.3 Recommendations: 50 References: 51 Appendixes 53 6 Developing EFL Learner's Awareness about Machine Translation Problems ( A Case Study of Faculty of Education, Hantoub, Gezira, Sudan, 2014) Mohamed Adam Faraj Allah Kuku M.A. in ELT, 2014 Department of English Language Hasaheisas University of Gezira Abstract The importance of Machine Translation in communities where more than one language is generally spoken, as these communities often experience in a high need for routine translation. The study aims at enhancing the classical MT models, to introduce syntactical knowledge in the pre- translation step by reordering the source side of the corpus, determining the potential of different language model (ML) enhancement techniques in order improve the performance and efficiency of MT, and to present a continuous – space LM, estimated in the form of an artificial neutral network. The study followed the Descriptive Analytical Method. A questionnaire is used as a tool of data collection (20 MA students). The sample has been chosen randomly for the study population. The collected data were analyzed by using computer programme (SPSS). Among the final findings there are many results; Machine translation is valid for certain absolutely students encounter difficulties when using MT, problems of using MA results from the programme. Machine translating suitable words training. MT spent more time in amending and substituting suitable words, students are not allowed to use MT in literary works there is a range of inability to translate accurately needs students to resort MT. and MT is publicly available through tools on the internet such as Google Translation, Babel Fish. The study recommends the followings; avoid using MT in translating long texts, revise all the materials if translated by MT, students should not depend completely on MT, Designing a well belt infrastructure to cope with ICT development, Enhance electronic systems to support translation programmes, students should not use machine permanently, teachers should be trained, MT spent more time in amending and substituting suitable vocabulary and students are not allowed to use MT in literary works. 7 8 CHAPTER ONE INTRODUCTION 1.0 BACKGROUND: Machine Translation is a field of computational linguistics that investigates the translation of texts from one human language to another, while Statistical Machine Technology, in contrast to many automatic rule-based translation systems, is a translation paradigm based on statistical learning techniques. Our world is currently in a period of globalization, which implies increasing interaction and the intertwining of different language communities. Information globalization extends to all corners of the world, and although English is becoming a universal second language, users in general still feel more comfortable in their own native language. Consequently, multi-linguality should be seen as a strategic issue for all companies aiming to play an important role in the future information society. Poysti’s1 states that ―you can always buy in your own language, but you must sell in your customer’s language―has become more and more relevant these days. A modern conception of social communications must include engaging customers, including commercial companies and users, in any information in its textual representation regardless of geography and cultural expectations. Another important aspect is the socio-political importance of translation in communities where more than one language is generally spoken, as these communities often experience a high need for routine translation. MT is particularly attractive for the European Union (EU) since it already experiences high demands in terms of translation; as of January 1, 2007, there are 23 official EU working languages, and there are significant 9 improvements have been achieved in machine translation (MT) over the past few years, mostly motivated by the appearance of statistical machine translation (SMT) technology, which is currently considered the best way to perform MT of natural languages. 1.5 Statement of the problem : The researcher noticed that, the majority of university students, tend to use computer in translating their language tasks in translation, without caring for what they take from these sites they do not confirm whether it is true or false, acceptable or not. For example, Google Translation gives as a crude, erroneous translation that doesn't follow the correct grammatical rules. The student's weak knowledge renders them unable to see these defects. This creates a problem. Another issue is how machine translation can be of use to minimize the translator's efforts in large scale enterprises. Because it is necessary to get help from the machine and then the translator interferes to amend the final draft. This creates a problem that may face graduates in their future when they depend mostly in those unconfirmed methods. 1.6 Objectives of the study: 1. for enhancing the production of MT 2. For introducing syntactical knowledge in the pre-translation step by reordering the source side of the corpus. 3. for improving the performance and efficiency of MT 4. For presenting continuous-space, estimated in the form of an artificial neural network. 1.7 Questions of the study : 1- What is the concept in machine translation? 2- What are the main problems that face students when using MT? 11 3- do the students gain benefits from using MT? 4- What are the advantages and disadvantages of using MT? 1.8 Hypotheses of the study 1. The student's awareness of language syntactically, semantically, and stylistically should be developed, or else they will not be able to amend errors of Machine Translation. 2. Machine Translation is badly needed for giving the gist of the text, and so minimizes the translator's effort and time. 3. The machine is indispensable for present day educational activities. 4. Some computer programs can find good translation, for single words and scientific learners. 5. MT is unable to convey idiomatic translation. 1.5 Significance of the study: The study tries to find out how best the students can make use of machine translation, and these necessities improving their competence in the four language skills. 1.6 Methodology: The researcher will follow the descriptive analytic method, for it is suitable for this type of research. 1.7 Limitations of the study: The study is limited to the students of Gezira University – Faculty of Education – Hasaheisa, 2014 11 Chapter two Literature Review 2.0 Introduction: Machine translation is a controversial issue. 2.1 Definition: Translation is an activity comprising the interpretation of the meaning of a text in one language — the source text — and the production, in another language, of a new, equivalent text — the target text, or translation. (Michael,2007) Traditionally, translation has been a human activity, although attempts have been made to automate and computerize the translation of natural language texts — machine translation — or to use computers as an aid to translation — computer-assisted translation.
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