Reem Bazal and Maha Atwi

Source Text إنهذهالشركاتتقومبدورأساسيوفاعلفيعمليةالعولمةوذلكمنخلالالاستثمارالمباشروتفكيكالعمليةالإنتاجيةوتكاملهادولياً،واشاعةنمطإستهلاكمحددوثقافةإستهلاكيةموحدةعلىصعيدالعالم،والسيطرةفيمجالالإعلاموالإعلانوالإتصالات. الفرعالثاني: منظمةالتجارةالعالميةواتفاقياتها انشئتمنظمةالتجارةالعالميةعام ١٩٩٥،وهيخليفةإتفاقية "الغات" وهيالإتفاقيةالعامةللتعريفاتالجمركيةوالتجارة،وقدابرمتفي ٣٠ تشرينالأول ١٩٤٨ ودخلتحيزالنفاذفيالأولمنكانونالثاني ١٩٤٨. فيجولةالأوروغواي ١٩٨٧-١٩٩٣ تمالتوصلإلى ٢٢ إتفاقاًدولياًبمافيهاالغات ١٩٤٨ وأصبحتتسمىالغات ١٩٤٨ تميزاًلهاعنالإتفاقيةالأصليةالتيأصبحتجزءًامنكلالاتفاقياتاللاحقة. وبالإضافةإلىتلكالإتفاقياتهناكسبعتفاهماتهدفتإلىتوضيحبعضالأحكامالواردةفيالإتفاقياتالدوليةوقدجاءتهذهالإتفاقيةوالتفاهماتفيصورةملاحقللإتفاقالمنشىءلمنظمةالتجارةالعالميةالمعروفبإتفاقمراكشوأصبحتبناءًعليه،شروطأومتطلباتالإنضمامإلىمنظمةالتجارةالعالميةتستندإلىقبولاتفاقياتوتفاهماتجولةالأوروغوايكحزمةواحدةوهيالإتفاقياتالتيتحكمالتجارةفيالسلعوالخدماتوالجوانبالتجاريةلحقوقالملكيةالفكرية. وسنعرضلاهمالإتفاقياتالتيتضمنتهاجولةالأوروغوايمعالتشديدعلىإتفاقية "التربس". 1 - إتفاقيةالزراعة: تنصعلىتحويلالقيودغيرالتعريفيةالمفروضةعلىالسلعالزراعيةإلىقيودتعريفيةومنثمتخفيضالتعرفةالجمركيةولوبنسبمتفاوتةوبمددزمنيةمختلفةللبلدانالمتقدمةوالبلدانالنامية،بمتوسط 36 بالمئةفيحالةالدولالمتقدمةو24 بالمئةللدولالناميةويتمإنجازهذاالتخفيضخلال 6 سنواتبالنسبةللدولالمتقدمةوعشرسنواتللبلدانالنامية،ولايلزمالاتفاقالدولالاقلنمواًبإجراءأيةتخفيضاتعلىتعرفتهاالجمركيةلوارداتهامنالسلعالزراعية. كمانصتالإتفاقيةعلىعدمتقديمأيةدعمجديدللصادراتالزراعيةوعلىتخفيضالدعمالذييقدمللصادراتمنالسلعالزراعيةبنسبة 36 بالمئةمنقيمتهوبنسبة 21 بالمئةمنحجمالصادراتالتيتستفيدمندعمالتصديرعلىأساسمتوسطماكانيتممندعمخلالالفترةمن ١٩٨٦ إلى ١٩٩٠. وذلكخلال ٦ سنواتبالنسبةللدولالصناعيةويتمتخفيضهذاالدعمبنسبة ٢٤ منالقمةو١٤ بالمئةمنالكميةبالنسبةللدولالناميةخلال ١٠ سنواتمنبدءتنفيذالاتفاقية. 2- إتفاقيةالملابسوالمنسوجات: وتنصعلىإدراجتجارةالمنسوجاتوألملابسضمنإتفاقيةمتعددةالأطراففيفترةتمتدإلىعشرسنواتتنقسمإلىأربعةمراحل: - 1995 المرحلةالأولى،وتبدأبتحرير ١٦ بالمئةمنالحجمالكليللوارداتمنالمنسوجاتوالملابسكماكانتعام 1990. - ١٩٩٥ - ١٩٩٨،المرحلةالثانيةتكونالنسبةفيها ١٧ بالمئة. - ١٩٩٨ - ٢٠٠٢المرحلةالثالثة،وتكونالنسبة ١٨ بالمئة. - ٢٠٠٢ - ٢٠٠٥المرحلةالرابعة،وتكونالنسبةالمتبقيةوهي ٤٩ بالمئة. وفيهذهالمراحلتلغىالحصصالكميةالتيكانتسائدةقبلجولةالأوروغواي. قدنصتالمادة (٨) بإنشاءجهازللمتابعةعلىتنفيذالأعضاءللإلتزاماتولاحكامهذهالإتفاقيةويتكونهذاالجهازمنرئيسوعشرةأعضاءوهوبمثابةهيئةدائماتشرفتجارةالأنسجةوالملبوساتويقومبفحصكافةالمعاييرالتيتتضمنهاشروطالإتفاقيةوموافاتالأعضاءبالنتائجويلتزمالأعضاءبقبولالتوصياتالتيتصدرعنجهازالمتابعة. وقدارفقتبهذهالإتفاقيةقائمةمطولةتشملكافةالمنتجاتالتيتخضعلأحكامهذهالإتفاقيةومواصفاتهاونسبمكوناتها. 3- إتفاقيةالتجارةفيالخدمات GATS)) وتغطيتجارةالخدماتكافة،وتحددمبادئوقواعدلتجارةالخدماتوجداولبالإلتزماتالتيتتعهدبهاالدولالأعضاءوهناكمفاوضاتجديدةبدأتبشأنتجارةالخدماتمنذاذار ٢٠٠١ إرفاقالإتفاقيةبمجموعةمنالملاحق،نصتالمادة (٢٩) علىاعتبرهاجزءًامكملاًللإتفاقية. وتشملهذهالملاحقالخدماتالماليةوالنقلالجويوالإتصالاتوحركةالعمالةبالإضافةإلىالإعفاءاتالخاصةبمنحالدولالأولىبالرعاية. وتنصالمادة (٢٥) منإتفاقيةالتجارةفيالخدمات GATS))،علىإعتبارالتعاونالفنيبيندولالأعضاءيمثلإحدىالضروراتالأساسيةلإنجاحجهودتحريرالتجارةالدوليةفيالخدمات. وفيهذاالخصوصتوفرنقاطالإتصالالمنصوصاليهافيالفقرة (٢) منالمادة (٤) توفيرالمعلوماتوالخدماتمنالموردينمنالأعضاءالذينيحتاجونإلىالمساعدةالفنيةللبلدانالناميةبهدفتمكنهامنتنفيذالإتفاقيةوتعديلمواءمةتشريعاتهاالوطنيةوفقاًلذلكبهدفزيادةمشاركةهذهالدولفيالتجارةالدوليةللخدمات. Machine Translation These companies play a key role and an actor in the process of globalization, through direct investment and the dismantling of the production process and integration internationally, and the rumor that a specific pattern of consumption and consumer culture standardized worldwide, and control in the field of media, advertising and communications. Section II: WTO and its agreements Established the World Trade Organization in 1995, a successor agreement “GATT“It is the General Agreement on Tariffs and Trade, was signed on 30 October 1948, and entered into force on the first of January 1948. In the 1987-1993 Uruguay Round was reached to 22 international agreements, including the GATT 1948, and became known as the GATT 1948 distinguished her from the original agreement, which became a part of all subsequent agreements. In addition to these agreements there are seven understandings aimed to clarify the following provisions contained in international conventions have come this agreement and understandings in the form of supplements to the agreement originator of the World Trade Organization , known by agreement Crash became Accordingly, conditions or requirements to join the World Trade Organization are based on the acceptance of agreements and understandings tour Uruguay as one package which agreements governing trade in goods and services and the commercial aspects of intellectual property rights. We will present the most important agreements contained in the Uruguay Round Agreement, with an emphasis on the “trips“. 1 - Agriculture Agreement: Provides for the transfer of non-tariff barriers imposed on agricultural commodities to the limitations of identifying and then reducing tariffs if to varying degrees and lengths of time are different for developed countries and developing countries , with an average 36 percent in the case of developed countries and 24 percent for developing countries and is accomplished this reduction through 6 years for developed countries and ten years for developing countries , the agreement does not need the least developed countries to make any reductions in customs tariffs for imports of agricultural commodities . As stated in the agreement not to provide any new support for agricultural exports and the reduction of subsidies provided to exports of agricultural commodities by 36 percent of its value and 21 percent of the volume of exports, which benefit from export subsidies based on the average they used to be of support during the period from 1986 to 1990. During 6 years for industrialized countries and this support is reduced by 24 of the top 14 percent of the amount for developing countries during the 10 years of the start of implementation of the Convention. 2 - Agreement clothing and textiles: It provides for the inclusion of trade in textiles and Ombus multiple Alotarapovi agreement within a period of ten years divided into four stages: 1995 - The first phase, and start editing the 16 percent of the total volume of imports of textiles and clothing as they were in 1990. - 1995 - 1998, the second phase where the ratio is 17 percent. - 1998 - 2002 the third phase and the ratio is 18 percent. - 2002 - 2005 the fourth stage, and be the remaining 49 percent. In these stages canceled the quota shares that were prevalent before the Uruguay Round. May Article (8) the establishment of a follow-up to implement the Members of the obligations and provisions of this Agreement consists of this device from the Head of the ten members which is a body always oversees trade in textiles and apparel and scans all of the criteria contained in the terms of the agreement Amovat Members results Oaltzm Members to accept the recommendations of the device follow-up. I have attached to this agreement includes a lengthy list of all the products that are subject to the provisions of this Convention and its specifications and proportions of components. 3 - the Convention on Trade in Services GATS)) Cover trade in services all , and sets out principles and rules for trade in services and schedules Balaltazmat undertaken by Member States and there are new negotiations began on Trade in Services since March 2001 to attach the agreement set of appendices , Article (29) on the deemed an integral part of the Convention . These supplements include financial services, air transport and communications and the movement of labor as well as exemptions for granting MFN. Article (25) of the Convention on Trade in Services GATS)), on the grounds of technical cooperation between Member States is one of the basic necessities for the success of efforts to liberalize international trade in services. In this regard, provide focal points set forth in paragraph (2) of Article (4) provide information and services from suppliers of Members who need technical assistance to developing countries in order to enable them to implement the agreement and modify the harmonization of national legislation in accordance with the aim of increasing the participation of these countries in trade international Services. Human Translation These companies perform a fundamental and effective role in the globalization process through direct investment, the dismantling and the international integration of the production process. Also by spreading specific consumption patterns, worldwide standardized consumer culture and by dominating the media, advertising, and communication fields.  Section Two: World Trade Organization and its Agreements World Trade Organization was established in 1995. It is the successor of the GATT convention and the general convention of trade and customs. It was signed on the 30th of October 1948, and entered into force on the first of January 1948. In the 1987-1993 Uruguay Rounds, 22 international Agreements were attained including the 1948 GAT convention which became known as the “GAT 1948”, as a way to distinguish it from the original agreement that became part of the subsequent agreements. In addition to these agreements, there were seven understandings that aimed to clarify some provisions cited in the international conventions. The understandings and the agreement came in the form of annexes to the originating convention of the World trade organization that is known as “Marrakesh Agreement”. According to it, the conditions or the requirements needed for joining the World Trade organization are based on the acceptance of the Uruguay Rounds agreements and understandings as a one package. These agreements are the one that govern the trade of goods and services and the commercial aspects of intellectual property rights. We will talk about the most important agreements that were included in the Uruguay Round Agreement with an emphasis on the “Trips Agreement”  The Agriculture Agreement: The agreement states on transferring imposed non-tariff barriers on agricultural commodities to identified tariffs and then reducing customs tariffs albeit in varying rates and different durations for developed and developing countries, with an average of 36 percent for developed countries and 24 percent for developing countries. This reduction is accomplished in six years in developed countries and ten years in developing ones. The agreement doesn’t bind the least developed countries to make any reductions on the custom tariffs of its imports of agricultural commodities. Also, the agreement stated on not providing any new subsidies for the agricultural exports and on scaling down the support of the agricultural commodities exports to 36 percent of its value and to 21 percent of the volume of exports which benefit from the support that was occurring from 1986 to 1990. This is scheduled to happen in six years for industrialized countries where the support will scale down to 24 percent from the value while it will scale down to 14 percent from the amount in developing countries after ten years of the implementation of the convention.  Clothing and Textiles Agreement: The agreement states on the inclusion of textiles and clothing trade with in a multilateral agreement in a period of ten years divided to 4 stages: 1995- First stage, starts by liberating 16 percent of the total volume of Textiles and clothing imports as they were in 1990. 1995-1998: second stage, where the ratio is 17 percent. 1998-2002, third stage, where the ratio reaches 18 percent. 2002-2005: fourth stage, it forms the remaining percent which is 49 percent. In these stages, the quota shares that were prevalent before the Uruguay Round are abolished. Article 8 stated on the establishment of a device to track the members’ implementation of this agreement’s obligations and provisions. This device is made up of a president and ten members. It serves as a body that oversees the trade of textiles and apparels and check all the criteria included in the terms of the agreement. It also provides the members with the results and binds them to accept the recommendations of the tracking body. With the convention came a long list of all the products that are subjected to the provisions of this agreement and its components’ proportions and specifications. Abstract In her text “Machine Translation System and Human Translation with economic texts (2013), ReemBazzal intend to discuss the proper use of available online machine translation technologies in economic translation and provide an objective view of the suitability and reliability of these systems in translation. To illustrate more, practical texts have been submitted and they were translated by both Machine Translation and Human Translation. The evaluation of the work of such technologies and of human translation came based to four different aspects: semantics, syntax, morphology and comprehension and they concluded that although Machine translation results are not that reliable, they can help in producing a well understood text and help in finding some terms and expressions related to the economic field.The incompatibility in semantics and syntax was clear due to the presence of improperly structured and wrongly defined sentences. Thus the writer indicates that economic texts translated by machine can achieve a high credibility when the syntactic and lexicon (semantic) aspects are fixed. This paper is set out to verify this belief. Commentary For a fair comparison of the performance of different online MT systems and Human Translation on economic texts, she needed an appropriate text that the MT systems can evaluate. The text she chose is made up of 625words in its Arabic version. It is therefore a reliable test set for examining the translation quality of economic texts by MT systems and human translation and to produce substantial statistical analysis for their performance in quantitative evaluation. She translated the text human translation and then used google translate to get the machine translation. The results were the following:  Semantics: When it comes to semantics, the meaning or the interpretation of a word or sentence we noticed that machine translation systems were able to give the exact economic definitions and phrases.There were some words that were translated differently between the human translation and the machine systems. Google translate gave lexical definitions of totally different words and sometimes it gave the same Arabic words but written in English letters which effected on the whole meaning of the sentence. On the other hand, human translation gave the exact meaning definition of the words. From the difference: Word or Phrase Human Translation Machine Translation دور اساسي Fundamental role Key role إتفاقيات Conventions Agreements تحرير Liberating Editing ألغى Abolished Canceled نصًّت Stated May وتنصعلىإدراجتجارةالمنسوجاتوألملابسضمنإتفاقيةمتعددةالأطراففيفترةتمتدإلىعشرسنواتتنقسمإلىأربعةمراحل The agreement states on the inclusion of textiles and clothing trade with in a multilateral agreement in a period of ten years divided to 4 stages: It provides for the inclusion of trade in textiles and Ombus multiple Alotarapovi فاعل Effective Actor As for the similarities, here are some examples: Word or phrase Human Translation Machine Translation دعم Subsidiaries Subsidiaries تعرفة جمركية Custom tariff Custom tariff المنسوجات Textiles Textiles القيود غير التعريفية Non-tariff barriers Non-tariff barriers سلع Commodities Commodities  Morphology: Concerning morphology, machine translation has a problem when it comes to translation related to Inflectional morphemes, the exact number, gender of the subject and the exact verb. When translating from Arabic to English, the agreement between grammatically linked items was often missing which led to some sentences that can’t be understood. While human translation has proved its efficiency in giving the exact verb tense number, possession, and comparison. Source text:تنصعلىتحويلالقيودغيرالتعريفيةالمفروضةعلىالسلعالزراعيةإلىقيودتعريفيةومنثمتخفيضالتعرفةالجمركيةولوبنسبمتفاوتةوبمددزمنيةمختلفةللبلدانالمتقدمةوالبلدانالنامية Machine translation:Provides for the transfer of non-tariff barriers imposed on agricultural commodities to the limitations of identifying and then reducing tariffs if to varying degrees and lengths of time are different for developed countries and developing countries Human Translation:The agreement states on transferring imposed non-tariff barriers on agricultural commodities to identified tariffs and then reducing customs tariffs albeit in varying rates and different durations for developed and developing countries. Source text:وقدارفقتبهذهالإتفاقيةقائمةمطولةتشملكافةالمنتجاتالتيتخضعلأحكامهذهالإتفاقيةومواصفاتهاونسبمكوناته Machine translation:I have attached to this agreement includes a lengthy list of all the products that are subject to the provisions of this Convention and it’s specifications and proportions of components. Human Translation:With the convention came a long list of all the products that are subjected to the provisions of this agreement and its components’ proportions and specifications. Source text:وبالإضافةإلىتلكالإتفاقياتهناكسبعتفاهماتهدفتإلىتوضيحبعضالأحكامالواردةفيالإتفاقياتالدوليةوقدجاءتهذهالإتفاقيةوالتفاهماتفيصورةملاحقللإتفاقالمنشىءلمنظمةالتجارةالعالميةالمعروفبإتفاقمراكشوأصبحتبناءًعليه Machine translation:international conventions have come this agreement and understandings in the form of supplements to the agreement originator of the World Trade Organization, Human translation: In addition to these agreements, there were seven understandings that aimed to clarify some provisions cited in the international conventions. The understandings and the agreement came in the form of annexes to the originating convention of the World trade organization that is known as “Marrakesh Agreement”  Syntax: Concerning the word order (syntax): the human translation is better than machine translation. The word combination in human translation is respected and well organized. It is more accurate and follows the grammatical rules: subject-verb and we can also notice the proper use of words such determiners, modifiers, and complements While in machine translation a majority of phrases started with the verb or the verb phrase instead of the noun, and the structure is most likely similar to the combination of words in the Arabic language, hence, the Arabic uses the : verb-subject-object combinational structure while in the English language, it is subject-verb-object- prepositional phrase (noun group, adjective, adverb ,prepositional, and possessive) so it’s obvious that google translate was unable to give good results for example: Source text:انشئتمنظمةالتجارةالعالميةعام ١٩٩٥ Machine translation:Established the World Trade Organization in 1995 Human translation:World Trade Organization was established in 1995 Source Text:وبالإضافةإلىتلكالإتفاقياتهناكسبعتفاهماتهدفتإلىتوضيحبعضالأحكامالواردةفيالإتفاقياتالدوليةوقدجاءتهذهالإتفاقيةوالتفاهماتفيصورةملاحقللإتفاقالمنشىءلمنظمةالتجارةالعالميةالمعروفبإتفاقمراكشوأصبحتبناءًعليه،شروطأومتطلباتالإنضمامإلىمنظمةالتجارةالعالميةتستندإلىقبولاتفاقياتوتفاهماتجولةالأوروغوايكحزمةواحدة Machine translation:known by agreement Crash became Accordingly, conditions or requirements to join the World Trade Organization are based on the acceptance of agreements and understandings tour Uruguay as one package which agreements governing trade in goods and services and the commercial aspects of intellectual property rights. Human translation: The understandings and the agreement came in the form of annexes to the originating convention of the World trade organization that is known as “Marrakesh Agreement”. According to it, the conditions or the requirements needed for joining the World Trade organization are based on the acceptance of the Uruguay Rounds agreements and understandings as a one package. Source text:وفيهذهالمراحلتلغىالحصصالكميةالتيكانتسائدةقبلجولةالأوروغواي. Machine Translation:In these stages canceled the quota shares that were prevalent before the Uruguay Round Human translation:In these stages, the quota shares that were prevalent before the Uruguay Round are abolished.  Comprehension and pragmatics: After comparing the two methods of translation we noticed that the target texts in the machine translation and despite the mistakes can be understood. But the use of grammar and punctuation is not correct and the sentences are sometimes lengthy and complex. Also, MT produces some sentences that are unfortunately far from the meaning given in the source text. As for human translation, the texts we well understood, the meaning was clearly stated in the target language and the use of grammar and punctuation is correct. Take the following sentences as examples: Machine Translation examples: May Article (8) the establishment of a follow-up to implement the Members of the obligations and provisions of this Agreement consists of this device from the Head of the ten members which is a body always oversees trade in textiles and apparel and scans all of the criteria contained in the terms of the agreement Amovat Members results Oaltzm Members to accept the recommendations of the device follow-up. Cover trade in services all , and sets out principles and rules for trade in services and schedules Balaltazmat undertaken by Member States and there are new negotiations began on Trade in Services since March 2001 to attach the agreement set of appendices Article (29) on the deemed an integral part of the Convention The existence of such non- understood sentences was somehow limited and the positive results that were found in the semantic field helped in making machine translation system good in translation when it comes to the translation of the economic texts. The existence of terminology and phrases that holds the exact economic definitions made google translate somehow reliable in translation. Yet the existence of syntax mistakes and wrong definitions of words made the level of compatibility around 40 %  Recommendations: 1. It is necessary to apply and add specific linguistic knowledge to the machine translation systems such as morphological analyzers, part of speech taggers, and full grammar for each language included in the system. This will ensure the production of grammatically correct sentences, correct syntax and improved terminology use. 2. It is important to allow the search of the machine system logs on-line in order to grant contrastive linguists and professional translators the possibility of evaluating everything from minor aspects of lexical usage and syntactic structure to the engine itself. Knowing that this will help users in using what other specialists have already corrected and put there. 3. It is recommended that computational linguists modify the economic lexicon when it comes to translating economic texts in order to insure the use of the exact terms, phrases and sentences in the translated version. 4. Machine translation must include professional memories in order to improve its work.  Conclusion: It is clear that machine translation technologies (google translate in our case) are useful in translation,linguistic analysis and in the preparation of a rough draft among many professional translators (Champollion, 2003; lagoudaki, 2008; O’Hagen and Ashworth, 2002) They are widely available and relatively free of charge. This paper shows how Mt can serve as a basis for training translators to work with these systems or to use them as a tool for finding terms and phrases like economic texts which in its turn also helps them save time. Yet, the disadvantages are still overcoming the advantages and the translation quality is still a little bit rough and lacks the lexical and syntactic touch making the MT systems tools for providing ordinary work of translation not impressive one. No perfection achieved while using such system  References: Benito,D.(2009). “ Future Trends in Translation Memory”. Atril, RevistaTradumatic- ISSN: 1578-7559 Bazzal, Reem (2013). The Performance of Machine Translation Systems and Human translation with Economic Texts. Lebanese International University. Issue 13

Breaking Translation Barriers in Politics

TRNS 303-Computer Assisted Translation Fall 2013-2014 Breaking Translation Barriers in Politics Submitted to: Dr. Ghada AWADA Ghina BOU CHAKRA ID# 11031438 Table of contents: Abstract……………………………………………………………………………...3 Document 1…………………………………………………………………………..4 Document 2……………………………………………...……………………….….8 Document 3……………………………………………...……………………….….8 Document 4……………………………………………...……………………….….8 Document 5……………………………………………...……………………….….8 Commentry…………..…………………………………………………………….29 A. Introduction……………………………………………………………29 B. Aims of MT…………………………………………………………….29 C. Human Translation vs Machine Translation :analytical study…….30 a. Endormement…………………………………………………..30 b. Refutation……………………………………………………..32 Recommandations ……………………………………………………………….....35 Conclusion…………………………………………………………………………..36 References……………………………………………………………………..……38 I. Abstract Bou Chakra, G. (2013) in the notation entitled “Breaking Translation Barriers in Politics,” stated the difference between machine and human translations using two sets of texts (English, Arabic) as input is stated, with the use of five examples of political documents for comparison. The Google translator is utilized as a source for the machine translation of the extracted articles, whereas the author herself translated the same editorials from the perspective of human translators. Accordingly, this paper diagnoses the faults and attempts to detect the reasons of translation, as it sheds light on the areas where the right interpreted solution is missed. Meanwhile, flaws and rendering problems are categorized and analyzed, with their coinciding recommendations proposed. The two modes of translation (from and into Arabic) face a wide range of common linguistic problems as well as mode-specific setbacks. As Arabic and English are distant languages from two unrelated families, machine translation is bound to face many dilemmas in producing meaningful coherent translations between the two. Consequently, this piece is an attempt to draw a distinction between the two types of translation while illuminating the different characteristics of each one. Document 1 Source Text Oliver: Publicly, Kennedy took full responsibility for the fiasco. Privately, he was furious at the Joint Chiefs “sons of bitches” and “those C.I.A. bastards.” threatening to shatter the CIA into a thousand pieces and scatter them to the winds. Incredibly, he fired Allen Dulles, albeit diplomatically and two other top officials, and all C.I.A. overseas personnel were placed under State Department control. Kennedy’s growing mistrust of his military and intelligence advisors made it easier to rebuff their pressure to send troops in 1961 into the tiny land-locked Asian nation of Laos, something that Eisenhower had warned him might be necessary to defeat the communists. Newsreel: Laos, strategic buffer state between the Red Bloc and free Asia is watched with concern by all the world. Oliver: The Joint Chiefs wanted Kennedy to give prior commitment to a large-scale invading force. Arthur Schlesinger, an aide and respected historian, later said. Arthur Schlesinger’s voice: After the Bay of Pigs, Kennedy had contempt for the Joint Chiefs. He dismissed them as “a bunch of old men.” He thought Lemnitzer was a dope. Oliver: And as a result Kennedy opted for a neutralist solution which angered the Pentagon. It would come back to haunt him. The mood was dark when Kennedy traveled to vienna to meet Khrushchev at their first Summit Conference that June of ‘61. Khrushchev berated the young president for America’s global imperialism. Khrushchev’s voice: We in the U.S.S.R. feel that the revolutionary process should have a right to exist. Oliver: The major issue for Khrushchev was Germany. What terrified him was the prospect of West Germany finally getting control over U.S. nukes deployed so close to the Soviet Union. And also by 1961, approximately 20% of the East German population some 2-1/2 half million people, had fled through the open border seeking a better life in West Germany. It was an open-sore humiliation for the Soviets, who now wanted a treaty recognizing two separate Germanys and the withdrawal of western forces from West Berlin. Khrushchev explained to an American journalist. Human translation: أوليفر: علنياً، تحمّل كينيدي المسؤولية الكاملة لهذا الفشل،لكنه في السر، كان غاضبًا جدًا من هيئة الأركان المشتركة السفَلة ورجال الاستخبارات الوضيعين وهدّد بتحطيم الاستخبارات إلى ألف قطعة وتركها لتطير في الهواء.وبشكل لا يصدق، طرد آلن دوليس، ولو بطريقة دبلوماسية فقط، ومسؤولين رفيعي المستوى ووضع جميع العاملين في الاستخبارات خارج البلاد بعهدة وزارة الخارجية. إن انعدام الثقة المتزايدة تجاه مستشاريه العسكريين والاستخباريين،سهل إيقاف ضغطهم لإرسال جنود عام ألف وتسعمئة وواحد ستين إلى لاوس، البلد الآسيوي الصغير جداً،والمحاط ببلدان أخرى من جميع الجهات. الأمر الذي لفت أيزنهاور انتباهه بأن هذا قد يكون ضرورياً لهزيمة الشيوعية. رجل:09:25 لاوس، البلد ذو الموقع الاستراتيجي بين الكتلة الحمراء وآسيا الحرة، يخضع لمراقبة بالغة الاهتمام من جميع العالم. أوليفر:09:31 أرادت هيئة الأركان المشتركة من كينيدي أن يقدم التزاماً مسبقاً بقوة هجومية ضخمة.آرثر شليزنغر، المساعد والمؤرخ المحترم قال لاحقًا... آرثر شليزنغر:09:43 بعد عملية خليج الخنازير، كان كينيدي منزعجًا من هيئة الأركان المشتركة واعتبرهم مجموعة من كبار السن، وأن ليمنتزر مجرد أحمق. ونتيجةً لذلك، اختار كينيدي حلاً وسطياً أثار غضب البنتاغون وعاد ليقض مضاجعه. أوليفر:10:04 كان الجو العام حين سافر كينيدي إلى فيينا للقاء خروتشيف مظلماً. وفي أول قمة بينهما في يونيو عام ألف وتسعمئة وواحد وستين، انتقدخروتشيف الرئيس الشاب بسبب إمبريالية أميركا العالمية. 10:20 خروتشيف نحن في الاتحاد السوفياتي، نشعر بأنه يحق للعمليات الثورية بالانطلاق. أوليفر:10:26 المشكلة الرئيسية بالنسبة لـ خروتشيف كانت ألمانيا. وما أرعبه هواحتمال أن تسيطر ألمانيا الغربية على الأسلحة النووية التابعة للولايات المتحدة الموجودة على مقربة من الاتحاد السوفياتي. وأيضًا،وفي عام ألف وتسعمئة وواحد وستين، هرب حوالى عشرين في المئة من سكان ألمانيا الشرقية، ما يقارب مليوناً ونصف مليون شخص، عبر الحدود آملين الحصول على حياة أفضل في ألمانيا الغربية. كان ذلك ذلاً علنياً للسوفيات الذين أرادوا معاهدة تقر بوجود دولتين ألمانيتين منفصلتين وانسحاب القوات الغربية من ألمانيا الغربية. شرح خروتشيف لصحافي أميركي. Google Translation: أوليفر: علنا، استغرق كينيدي المسؤولية الكاملة عن الفشل الذريع. القطاع الخاص، وقال انه كان غاضبا في "أبناء الكلبات" هيئة الأركان المشتركة و"تلك CIA الأوغاد. "يهدد لتحطيم وكالة الاستخبارات المركزية إلى ألف قطعة وتبعثرها للرياح. بشكل لا يصدق، انه اطلق النار ألين دالاس، وإن كان دبلوماسيا واثنين من كبار المسؤولين، وجميع CIA وضعت الموظفين في الخارج تحت سيطرة وزارة الخارجية. جعل عدم الثقة كنيدي متزايد من مستشاريه العسكريين والمخابرات من الاسهل للرد ضغوطهم لارسال قوات في عام 1961 في الدولة الصغيرة غير الساحلية الآسيوية في لاوس، وهو الأمر الذي حذرت منه أيزنهاور قد يكون من الضروري لهزيمة الشيوعيين. نشرة إخبارية: لاوس، وشاهد دولة عازلة الاستراتيجية بين كتلة الأحمر وخالية آسيا بقلق من جميع أنحاء العالم. أوليفر: إن هيئة الأركان المشتركة أراد كينيدي لإعطاء التزام قبل قوة غازية على نطاق واسع. وقال آرثر شليزنجر، مساعد ومؤرخ محترم، في وقت لاحق صوت آرثر شليزنجر: بعد خليج الخنازير، وكان كينيدي ازدراء لهيئة الأركان المشتركة. انه وصفها بأنها "مجموعة من كبار السن من الرجال"، ويعتقد ان Lemnitzer على منشطات. أوليفر: ونتيجة لذلك اختارت كينيدي عن حل المحايد الذي أغضب البنتاجون. فإنه يعود ليطارده. كان مزاج الظلام عندما سافر إلى فيينا كينيدي لتلبية خروشوف في المؤتمر القمة الأولى بهم أن شهر يونيو من '61. خروتشوف وبخ الرئيس الشاب للإمبريالية العالمية في أميركا. صوت خروشوف: ونحن في الاتحاد السوفياتي يشعرون بأن العملية الثورية ينبغي أن يكون لها الحق في الوجود. أوليفر: كان قضية رئيسية بالنسبة للخروتشوف ألمانيا. ما بالرعب وسلم كان احتمال الحصول على ألمانيا الغربية في نهاية المطاف السيطرة على الأسلحة النووية الأمريكية المنتشرة على مقربة من الاتحاد السوفياتي. وأيضا من قبل عام 1961، ما يقرب من 20٪ من سكان ألمانيا الشرقية بعض 2-1/2 نصف مليون شخص، فروا عبر الحدود المفتوحة بحثا عن حياة أفضل في ألمانيا الغربية. كان والإذلال مفتوح للالتهاب السوفييت، الذين كانوا يريدون الآن معاهدة تعترف الألمانيتين منفصلة وانسحاب القوات الغربية من برلين الغربية. وأوضح خروتشوف لصحفية أمريكية. Document 2 Source Text Elected to the Senate in ‘52, Kennedy had been a Cold War liberal who had avoided criticizing Joseph McCarthy, an old family friend. His younger brother Robert had even served on McCarthy’s staff. Alluding to the title of his Pulitzer Prize winning book “Profiles in Courage…” Eleanor Roosevelt said she wished that Kennedy had “had a little less profile and a little more courage." His team, a combination of insiders from foundations, corporations and Wall Street firms, as well as progressives and intellectuals, was labeled “the best and the brightest” for their intelligence, achievements and can-do spirit, typified by National Security Advisor McGeorge Bundy, the first applicant to get perfect scores on all three Yale entrance exams. At Defense, Kennedy brought in a civilian outsider, Robert McNamara. Renowned for his computer-like mind and leading the Ford Motor Company, he quickly earned the immediate distrust of his generals by putting the Pentagon under microscopic scrutiny. A devastating nuclear war plan had been handed down to them from Eisenhower. McNamara was appalled by what he found--a culture of paranoid worst-case scenarios. When Kennedy asked the statistically-minded McNamara to ascertain just how big the missile gap really was, it took three weeks to confirm that there was no gap and several months to find out that there was quite a huge difference. The U.S. had approximately 25,000 nuclear weapons, the Soviets, 2,500. Human translation: انتُخب لمجلس الشيوخ عامألف وتسعمئة واثنين وخمسين، وكان كينيدي ليبراليًا مؤيداً الحرب الباردة.وتفادى انتقاد جوزيف مكارثي، صديق العائلةالقديم.حتى إن أخاه الأصغر، روبرت، عمل ضمن فريق عمل مكارثي.وقالت إلينور روزفلت مشيرةإلى عنوان كتابه الذي حاز جائزة بوليتزر "لمحات منالشجاعة"إنها تمنت لو أن كينيدي كان أقل وسامة وأكثر شجاعة. ولُقّب فريق عمله الذي ضممجموعة من المنتمين إلى منظمات وشركات عادية ومالية في وول ستريت،بالإضافة إلى تقدميين ومفكرين، بأنهالفريق "الأفضل والأذكى" لأجل معلوماتهم وإنجازاتهم وروحهم الحماسية. ورَمَز إليهم مستشار الأمن القومي ماكجورج بندي،وهو أول مرشح يحصل على مجموع كامل في امتحانات الدخول الثلاثة إلى جامعة يال. وأتى كينيدي إلى وزارة الدفاع برجل مدني من خارج حقل السياسة، روبرت ماكنمارا، وهوالمعروف بفكره الذي يشبه الحاسوب بقيادة شركة فورد.وكسب على الفور عدم ثقة جنرالاته حين عرّض البنتاغون لفحص دقيق جداً. تسلّمواخطة مدمّرة لحرب نووية من أيزنهاور،وصُعق ماكنمارا بما وجده.إنها ثقافة الخوف في أسوأ الحالات. وحين طلب كينيدي من ماكنمارا ذي العقل الإحصائي أن يحدّد مدى عمق فجوة الصورايخ،احتاج الأخيرلثلاثة أسابيع حتى يؤكد عدم وجود أيّ فجوة،ولعدة أشهر ليكتشف الفرق الشاسع.امتلكت الولايات المتحدة خمسة وعشرين ألف سلاح نووي تقريباً فيما امتلك الاتحاد السوفياتي ألفين وخمسمئة سلاح نووي.امتلكت الولايات المتحددة ألفاً وخمسمئة طائرة حربية. Google Translation: انتخب لعضوية مجلس الشيوخ في '52 ، كان كينيدي كان ليبراليا الحرب الباردة الذين تجنبت انتقاد جوزيف مكارثي ، وهو صديق للعائلة القديمة. وكان شقيقه الأصغر روبرت خدم حتى على الموظفين مكارثي . في إشارة إلى لقب له الفوز بجائزة بوليتزر كتاب " لمحات في الشجاعة ... " وقال اليانور روزفلت أعربت عن رغبتها أن كينيدي كان "كان أقل قليلا صورة و أكثر من ذلك بقليل الشجاعة. " فريقه ، وهو مزيج من المطلعين من المؤسسات والشركات و شركات وول ستريت ، وكذلك التقدميين و المثقفين ، وصفت " أفضل و ألمع " ل ذكائهم والإنجازات و يمكن أن تفعل الروح، تتميز مستشار الأمن القومي ماك جورج بوندي ، وطالب أول من يحصل على درجات الكمال على جميع امتحانات القبول ييل الثلاثة. في الدفاع ، جلبت كينيدي في الخارج المدنيين، روبرت ماكنمارا . تشتهر عقله مثل الكمبيوتر و الرائدة في شركة فورد للسيارات ، وقال انه حصل بسرعة انعدام الثقة فورا من جنرالاته عن طريق وضع البنتاغون تحت المجهر المجهرية. وقد تم تسليم خطة الحرب النووية المدمرة نزل إليهم من ايزنهاور . ذهلت مكنمارا من خلال ما وجد - ثقافة سيناريوهات أسوأ حالة بجنون العظمة . عندما سئل كينيدي إحصائيا في التفكير ماكنمارا للتأكد من مدى كبيرة كانت الفجوة الصواريخ حقا ، استغرق الأمر ثلاثة أسابيع للتأكد من وجود فجوة و عدة أشهر لمعرفة ان كان هناك فرق كبير جدا . وكان ما يقرب من 25،000 الولايات المتحدة الأسلحة النووية ، السوفيات ، 2،500 II. Commentary A- Introduction Background Much has been said about translation as being one of the most effective, if not the only means of communication especially among cultures of different languages. Translation as a concept existed hundreds of years ago, but only during the second half of the 20th century did it emerge as an independent academic field called “Translation Studies” and from there it began being taught at universities. Therefore, a dire need for translation as an educational specialty has prompted theorists in the field to seek for more sophisticated methods and techniques for a way of quicker, cheaper and more effective way of translation. Thus, a new type emerged and evolved, as a competitor with human translators; dubbed “Machine Translation’ or the “Automatic Translation.” B- Aims of Machine Translation Most translations in the world are not of texts which have high literary and cultural status. The great majority of professional translators are employed to satisfy the huge and growing demand for translations of scientific and technical documents, commercial and business transactions, administrative memoranda, legal documentation, instruction manuals, agricultural and medical text books, industrial patents, publicity leaflets, newspaper reports, etc. Some of this work is challenging and difficult. But much of it is tedious and repetitive, while at the same time requiring accuracy and consistency. The demand for such translations is increasing at a rate far beyond the capacity of the translation profession. The assistance of a computer has clear and immediate attractions. The practical usefulness of an MT system is determined ultimately by the quality of its output. But what counts as a ‘good’ translation, whether produced by human or machine, is an extremely difficult concept to define precisely. Much depends on the particular circumstances in which it is made and the particular recipient for whom it is intended. Fidelity, accuracy, intelligibility, appropriate style and register are all criteria which can be applied, but they remain subjective judgments. What matters in practice, as far as MT is concerned, is how much has to be changed in order to bring output up to a standard acceptable to a human translator or reader. With such a slippery concept as translation, researchers and developers of MT systems can ultimately aspire only to producing translations which are ‘useful’ in particular situations — which obliges them to define clear research objectives — or, alternatively, they seek suitable applications of the ‘translations’ which in fact they are able to produce. C- Human Translation VS Machine Translation: An analytical study 1- Endorsement (with Google translation) Since the advent of the 21st century, there have been a lot of developments and new technologies have been introduced which have made life more convenient and simple. A machine translator is such a small yet useful device. Machine translation, which is also known as Computer Aided Translation, is basically the use of software programs which have been specifically designed to translate both verbal and written texts from one language to another. Let's go over the advantages of machine translation (Dilmanc, 2011) 1.1-Grammar From this angle, there are no major mistakes in the translation of Google regarding plural, singular, or verb tenses. However, verb tenses have to be chosen in way that preserves the meaning of the sentence. So from grammatical point of view the sentences translated by Google may be correct, but the meaning may differ if the verb tense is not well chosen. This case may be found in literary text which contains the variety of verb tenses, and, usually, it is not the case in journalistic texts. 1.2-Proper Nouns A noun belonging to the class of words used as names for unique individuals, events, or places is a proper noun; also called proper name. Despite the fact that machine translation is full of errors, there is a very significant benefit of it. Not all human translators know the exact translations of proper nouns. For example, " Pulitzer Prize" was correctly translated via Google to :"" بجائزة بوليتزر. 2- Refutation (with human translation) As no one can deny that the main rationale behind any translation is to transfer as much as possible the meaning intended by the source text's writer into the target text, It is quite obvious, from the reading of the human and machine translation of each source text, that machine translation sometimes achieves an ambiguous and distorted meaning which becomes difficult to grasp it and that it is not that perfect rendering of the source text into the target text. 2.1-Semantics According to Jean, S. (2000), Semantics is the study of the meaning. It focuses on the relationship between signifiers, such as words, phrases, and symbols, and what their stand for, i.e. their denotation. A semantic study of the above mentioned texts can reveal that the meaning is highly maintained in Human Translated texts whereas it is violated in Machine Translated texts just like in the following example. The sentence "Incredibly, he fired Allen Dulles, albeit diplomatically" was translated by Google as the following بشكل لا يصدق، انه بشكل لا يصدق، انه اطلق النار ألين دالاس، وإن كان دبلوماسيا. However, the translation done by human for this sentence is وبشكل لا يصدق، طرد آلن دوليس، ولو بطريقة دبلوماسية فقط،. Another example, the sentence "He thought Lemnitzer was a dope." was translated by Google as the following ويعتقد ان Lemnitzer على منشطات. However, the translation done by human for this sentence is أعتبر أن ليمنتزر مجرد أحمق. In these examples, the machine translated sentence produces certain associations sometimes with no sense. This is mainly, as stated before, due to the fact that machine translation focuses on the source text's language which is in this case English, as being different from Arabic. Thus, Google machine translator does not give options or variable choices while translating; it just translates word for word without dealing with the whole meaning of the text. As for the human translation in the same example, the ability of the translator to substitute the words renders the translation easy to be understood. It is only through human translation that the translator can add or delete certain words or even phrases, sometimes, for the sake of clarity. 2.2-Syntax According to Noe, N. (2002), syntax is the study of the principles and rules for constructing sentences in natural languages. The term syntax also refers to the rules and principles that govern the sentence structure of any language. Because each language has its own syntax, the sentence structure will not always be as it is in translating from one language to another. English-Arabic translation difficulties result from differences in word order between the syntax of the two languages. For example, the adjectives in English precede the nouns, while in Arabic, nouns precede the adjectives. Indeed, no machine translation can copy the same syntax from a target text to a source text. From this angle, what was noticed is that machine translations had mistakes, as in many areas the arrangement of words was not in an understandable `Arabic` pattern. An example of this is the sentence "The Joint Chiefs wanted Kennedy to give prior commitment to a large-scale invading force. Arthur Schlesinger, an aide and respected historian, later said" which was translated by Google as إن هيئة الأركان المشتركة أراد كينيدي لإعطاء التزام قبل قوة غازية على نطاق واسع.. Here we can clearly see the difference in dealing with grammatical accordance (subject verb disagreements) in the text and keeping the whole meaning of the sentence. 2.3-Morphology According to Aronoff, M. (1976), Morphology is the branch of linguistics that studies words; it is concerned with the internal structure of words as well as the relationships that exist among the words of the language. A good translation must be free of morphological errors which are mainly grammatical ones. Consistency also comes under morphology. An example of this is the sentence " Kennedy’s growing mistrust of his military and intelligence advisors made it easier to rebuff their pressure to send troops in 1961 into the tiny land-locked Asian nation of Laos, something that Eisenhower had warned him might be necessary to defeat the communists" which was translated by Google as جعل عدم الثقة كنيدي متزايد من مستشاريه العسكريين والمخابرات من الاسهل للرد ضغوطهم لارسال قوات في عام 1961 في الدولة الصغيرة غير الساحلية الآسيوية في لاوس، وهو الأمر الذي حذرت منه أيزنهاور قد يكون من الضروري لهزيمة الشيوعيين. . Although the meaning maybe can be comprehensible; nevertheless, the structure of languages are different and, hence, they should be respected for the sake of producing a well-formed translation in the target language. The inability of the machine translation to produce a well-structured text is due to its focus on the "comprehension" and not "the production of a perfect target text". So far as the human translation is concerned, the above example can reveal, clearly how the human translator is capable of avoiding what have been criticized in the machine translation. The human version is a structure respecting and its focus has been in both the source text, in an act of comprehension, and the target text, in an act of producing a perfect translation. The human translator's flexibility allows them to move from language into another bearing in their minds the difference of structures between languages. 2.4-Mechanics The right choice of words and terminologies is the secret behind a successful translation of any document, but machine cannot decide what term suits better this or that context (Hartmann, 1980). Any deviation from the genre of the given document is considered a big mistake. In that cause, Google doesn’t choose the accurate word like in the human translation. For example, in this sentence “Privately, he was furious at the Joint Chiefs..." the word “Privately” in English was translated by Google into the word “القطاع الخاص”, and it gave a completely different meaning which should be "secretly". Another example, in the sentence "Kennedy took full responsibility" the word :took" was translated by Google as استغرق which doesn’t match with the noun for it is meant to assume responsibility and not to took or spend time so it should be translated as تحمل. 2.5-Acronyms As for acronyms Google translation fails to analyze and give the correct translation for these acronyms. As an example, in the text used the acronym CIA was mentioned which stands for Central Intelligence Agency and should be translated asوكالة الإستخبارات المركزية but the machine kept it as it is, without rendering and that could be ambiguous for the target reader who might not know what is the CIA. III. Recommendations After viewing and analyzing the above points, on the different and common aspects between these two very competitive types of translation, the following recommendations can be suggested: When it comes to machine translation remember these three important rules: • Always do updates for the latest terminologies used in politics of the different countries because they differ depending on the culture, custom, and traditions of each country. • Take additional training courses in translation software; it helps to be more productive when knowing how to use the software properly and fluently. • Have more knowledge about politics and always follow up with what is going around nationally and internationally. While in general, other points can help in regards to translation itself, including: • It is imperative that a translator be alert to the particularity of each language and knows how to deliver the same meaning without any misunderstanding. • A translator should also be objective in his translation so that his personal point of view will not influence the purpose of the main text. • Translators need to accept the new technologies and learn how to use them to their maximum potential as a means to increased productivity and quality improvement. • Fully understand the political stance of the country you are translating about. IV. Conclusion Computer code as a universal language may at one point be able to transcend human language structure and software programs may become intelligent enough to truly understand language. However, humans are somewhat illogical beings and language is an adaptable, ever-changing, living concept that reflects the human psyche which may never be entirely captured in its essence by a machine. Computers and powerful software programs will play an increasing role in inter-language communication and will become more effective in bridging language gaps. Going forward it will remain important to be cognoscente of the limitations of software programs and machines, work around the flaws, embrace the benefits and add the human touch where necessary; so that one is not at risk to “step under floating burdens” which is Google translate for “stand under suspended loads” (Kakase, 2011, p. 2). You never know when the tower may be tumbling down and then, everyone will benefit from speaking more than just one’s own language. \ V. References Jean, S. (2002). Assessment of a good translation. British Journal of Guidance and Counseling. 12 (2), 434-898 Doi: 10.1080/15388220.2020.483182. Noe, N. (2002). Rules of English grammar. The language journal. October 28, 2013. Retrieved from http://www.thelanguagejournal.com/2004/05/08/opinion. Kakase, K. (2011, February 21). Google, Yahoo! BabelFish use math principles to translate documents online. Science News. Online newspaper, . Retrieved March 2, 2011, from http://www.washingtonpost.com/wp- dyn/content/article/2011/02/21/AR2011022102191.html?referrer=emailarticle Sajan, R. (2012).Retrieved from: http://www.sajan.com/blog/scary-translation mistakes-to-howl-about-and-how-you-can-avoid-them. Cambridge. (2013).Cambridge Studies. Retrieved from: http://www.c-s-p.org/flyers/978-1-4438-1677-9-sample.pdf.

The Performance of Machine Translation System and Human Translation with Political texts” (2013), Reem Bazzal, Maha Atwi,Nour Al Onies, Inaam Kotiesh and Ghina Khamis

Abstract In their text “The Performance of Machine Translation System and Human Translation with Political texts” (2013), Reem Bazzal, Maha Atwi,Nour Al Onies, Inaam Kotiesh and Ghina Khamis intend to discuss the proper use of available online machine translation technologies and human in political translation and provide an objective view of its suitability and reliability. They examined the services of such technologies through the use of google translate translation and of the human translation andevaluated their work from four different linguistic aspects: syntax, morphology, semantics and comprehension. Atwi, Bazzal, Khamis, Kotiesh and Onies concluded that although machine translation systems are useful and largely utilized in economic, journalistic and literal fields, they cannot be used as a resource for translation when it comes to political texts mainly because of the incompatibility in semantics and pragmatics for they give improperly defined words andgrammatically wrong sentences. This paper is set out to verify this belief. Commentary To illustrate more, practical text has been submitted and it was translated by the Machine Translation which is google translate and by a human translation. The text they chose العولمة is made up of 250 words in its English version. It is therefore a reliable text set for examining the translation process and the linguistic rules translation ofpolitical text by MT systems and to produce substantial statistical analysis for their performance. After translating the text,the results were the following: Semantics: When it comes to semantics, the meaning or the interpretation of a word or sentence we noticed that unfortunately, machine translation translated some words and expressions literally and gave different meanings and translation too. For example Source text: Human Machine العولمة globalization العولمة مقابلات equivalents interviews تعميم generating circular heye عالمي worldwide the whole أجاز allow to leave use توجيهاواحدا one direction directed guidance مجمعاللغةThe Academy ofThe Arabic توسيعspreadexpanding لعربيةفيالقاهرة The Arabic Language Language Academy in Cairo In Cairo مصطلح term word توجيها sharing guidance كوكبة Planetary constellation Syntax: Concerning the word order, the human translation showed impressive results in giving proper sentences that follows the grammatical rules: Subject – Verb- Object ( in translation to English) and in the use of modifiers and determiners while when it came to machine translation. The sentences were weak, lengthy and didn’t follow the grammatical rules. • Source Text: و قد قرر مجمع اللغة العربية في القاهرة إجازة إستعمال كلمة العولمة Human Translation:The Academy of the Arabic Language in Cairo had decided to allow the use of the word globalization Machine Translation: and has decided the Arabic Language Academy in Cairo leave use the word globalization. • Source Text: الحقانهمنالصعببمكان،إعطاءتعريفدقيقللعولمة بسببكثرةالتعريفاتبشأنها Human Translation:It is quite difficult to give a precise definition of “Globalization” because it has so many definitions Machine Translation:Right it's very difficult, to give a definition precise of globalization because of the large number of definitions which Morphology: Concerningmorphology, machine translation has a problem when it comes to translation related to Inflectional morphemes, the exact number, gender of the subject and the exact verb. When translating from Arabic to English, the agreement between grammatically linked items was often missing which led to some sentences that can’t be understood. While human translation has proved its efficiency in giving the exact verb tense number, possession, and comparison. Examples: • Source Text: الإنكليزية, و التي تعني تعميم الشيء و توسيع دائرته ليشمل الكل العولمة هي إحدى المقابلات العربية لكلمة globalization Human Translation: “globalization is one of the Arabic equivalents of the English word “Globalization” that means generating and spread a thing Machine Translation: Globalization is one of the interviews; the Arabic word for the English and globalization means which circular Heye and expanding his circle to include the whole. Source Text: وقدقررمجمعاللغةالعربيةفيالقاهرةإجازةإستعمالكلمةالعولمة، بمعنى جعل الشيء عالما واحد، موجها توجيها واحدا في إطار حضارة واحدة و لذلك قد تسمى الكونية او الكوكبة Human Translation: The Academy of the Arabic Language in Cairo had decided to allow the use of the word “العولمة” that signify making something on an international level. Thereupon, globalization is an expression that connotes the idea of turning the world to a one single world, heading to a one direction of sharing one civilization so it might be called Cosmic or Planetary concept. Machine Translation: and has decided the Arabic Language Academy in Cairo leave use of the word globalization, in the sense to make global thing. if the term globalization means making the world on world, one direct guidance in the context of one civilization may therefore called cosmic or constellation. Comprehension: Differences العولمةهياحدىالمقابلاتالعربيةلكلمة (globalization) الانكليزية The machine translation result:Globalization is one of the interviews, the Arabic world for the English and globalization While human translation:Globalization • The original text:تعنيتعميمالشيءوتوسيعدائرتهلتشملالكل Machine translation:Which means circular Heye and expanding his circle to include the whole Human translation: That means generating and developing a thing to become as a unit. • The original text: العولمةاذامصطلحيعنيجعلالعالمعالماواحدا Machine translation:If the term Globalization means making the world one world. Human Translation:Globalization is a term that means turning the world to one unit. Analysis From here, we can find that the human translation is different than the machine translation; for the human translator has a mind and can comprehend and know how to make his article coherent and free of errors. The machine translated documents in the political field are incoherent and lack the sense of comprehension and grammatical coherence. There are many differences between human translation and machine translation, in which errors regarding morphology, syntax, semantics, mechanics, coherence and comprehension are being found. The word choice in machine translation is very weak and the meaning is sometimes vague unlike the human translation which possesses an excellent word choice and uses exact terms that makes the meaning clear. The word order in machine translation is unorganized which makes the sentence barely readable whereas in human translation the word order is well-organized which makes the sentence very clear. Moreover, machine translation has weak grammar such as in sentence structure. . So in machine translation a lot of grammar mistakes are made while a human translator avoids the grammatical mistakes. In human translation the original text is 90% compatible with the target text whereas in machine translation it is 50% compatible, the text might be explicable but barely readable. Recommendation Political translation is a challenging one; it requires highly specialized terminology which can't be comprehended by the translator easily. Specialized translators in the political field also face many problems in translating these documents for what they need from paying attention to every little letter, since any change in the translation may change the whole context; hence most of the translators depend on the machine to find out the specialized terminology. Although the machine helps translators translate their documents using the most accurate terms, they can't depend on it completely since it doesn't comprehend the grammatical, structural and comprehensive errors, so if the translator pays attention to these errors, the document will be a high-quality one, it will contain the most accurate terms, finished in less time, earning high revenue, and will be a reliable one. Conclusion It was conspicuous that the machine translated documents are incoherent and full of grammatical and structural errors, but the reader is on the safe side for the terms are accurate and the sentences can be easily comprehended. Although some decoys can be found in the machine translated documents because of the structural changes, these are no more than 40% of the whole document, hence here comes the role of the human translator to detect the errors and correct them. And whenever the translator do his job in a way using his translating skills with the help of the machine, his job will be achieved perfectly without any errors or changes in the meaning. References: Atwi.Maha, Bazzal. Reem, Khamis. Ghina, Kotiesh. Inaam and Onies. Nour. (2014). “The Performance of Machine Translation System and Human Translation with Political texts”. Lebanese International University. Issue 12

Reem Bazzal, and Nour Onies

Abstract In their text Evaluation of Machine Translation System and Human Translation with Literary texts (2013), Reem Bazzal, and Nour Onies intend to discuss the proper use of available online machine translation technologies in literary translation and provide an objective view of the suitability and reliability of these systems in translation. To illustrate more, practical text has been submitted and it was translated by both Machine Translation and Human Translation. They evaluated the work of such technologies and of human translation from four different aspects: semantics, syntax, morphology and comprehension and concluded that although Machine translation results are not that reliable, they can help in producing a well understood text. This paper is set out to verify this belief. Comprehension For a fair comparison of the performance of different online MT systems and Human Translation on literary texts, they needed appropriate text that the MT systems can evaluate. The text they choseThe Raven by Edgar Allan Poe is made up of 406 words in its English version. It is therefore a reliable test set for examining the translation quality of literary texts by MT systems and human translation and to produce substantial statistical analysis for their performance in quantitative evaluation. After translating the text by both human translation and machine translation which is google translate, we concluded the following: Semantics: When it comes to semantics, the meaning or the interpretation of a word or sentence we noticed that there are differences and similarities between the human translation and the machine translation. For example, in human translation, the expression midnight dreary was translated into ليلةٍ مقفرة while google translate translated it into ليلة كئيبة. Another example is the word pondered which in human translation meant تأملت while in machine translation it was translated to فكرت. “Rapping at my chamber door" was translated into “يقرع علىبابمخدعي" in human translation while with google translate it was translated to "موسيقىالرابفيبابحجرتي Syntax: Concerning the word order (syntax): the human translation is better than machine translation. The word combination in human translation is respected and well organized. It is more accurate and follows the grammatical rules: subject-verb and we can also notice the proper use of words such determiners, modifiers, and complements while in machine translation a majority of phrases started with the verb or the verb phrase instead of the noun. For example: Source sentence: And the silken sad uncertain rustling of each purple curtain Thrilled me Machine translation: وحريريسرقةمؤكدحزينةلكلستارارجواني Human translation: الحفيفُالحريريُّالحزينُوالغامضُلكلِّستارةٍأرجوانية أثارني Source sentence: While I nodded, nearly napping, suddenly there came a tapping Machine translation: بينماكنتضربةرأس،القيلولةتقريبا،فجأةهناكجاءالتنصت، Human translation: وعندماسقطرأسيعلىصدريوأوشكتُأنأغفو فجأةًجاءَالطرقُ Morphology: Concerning the morphology, machine translation has a problem when it comes to translation related to Inflectional morphemes, the exact number, gender of the subject and the exact verb. When translating from English to Arabic, the agreement between grammatically linked items was often missing which led to some sentences that can be hardly understood. While human translation has proved its efficiency in giving the exact verb tense number, possession, and comparison. For example: Source text: While I nodded, nearly napping, suddenly there came a tapping Human translation: وعندماسقطرأسيعلىصدريوأوشكتُأنأغفو Machine translation: بينماكنتضربةرأس،القيلولةتقريبا،فجأةهناكجاءالتنصت، Another example on the wrong morphological interpretation that was clearly stated in the translation process: Source text: As of someone gently rapping, rapping at my chamber door. Human translation: وكأنأحداًبرفقٍيقرعُ...يقرعُعلىبابِمخدعي Machine translation: اعتبارامنبعضواحدموسيقىالراببلطف،موسيقىالرابفيبابحجرتي After comparing the two methods of translation we noticed that the target texts in the machine translation and despite the mistakes can be understood. But the use of grammar and punctuation is not correct and the sentences are sometimes lengthy and complex. Also, MT produces some sentences that are unfortunately far from the meaning given in the source text. As for human translation, the texts we well understood, the meaning was clearly stated in the target language and the use of grammar and punctuation is correct. Take the following sentences as examples: Source sentence: Once upon a midnight dreary Machine Translation:مرةواحدةعندمنتصفالليلالكئيب Human Translation:فيليلةٍ مقفرةٍعندمنتصفالليل Source sentence: Over many a quaint and curious volume of forgotten lore Machine Translation:أكثرمنوحدةتخزينالعديدغريبةوغريبةمنالعلمالنسيان Human Translation مررتُبعديدٍ منالمعتقداتِالقديمةِالغريبة التيغطاهاألنسيان Source sentence: distinctly I remember it was in the bleak December Machine Translation:بوضوحتذكرت،أنهكانفيديسمبرالقابض Human Translation:أتذكّرُبوضوحٍ إنه ديسمبرالكثيب Source sentence: the rare and radiant maiden whom the angels name Lenore Machine Translation: النادرةالمتألقةالنادرةالذينلينوراسمالملائكة Human translation: لتلكالفتاةِ الرائعةِالمتألقة التيأسمتهاالملائكةُُلينور Recommendations It is important to include in MT engines special lexicon domains that can be used in literal translation, which offers quite a wide variety of lexicons if one accesses the MT sites directly. It is necessary to take into consideration that on-line MT engines are aimed at helping users deal with ephemeral literary texts and they help communication in many situations. 1. It is important to understand that machine translation has definitely improved the work of journalistic translation whether by the use of blogs, emails or portables like new Samsung phones (S. Translator) and IPhone phones( I translate) and the intelligent use of them led to the focus of the best human efforts where they should be. Machine translation like blogs and iPad and S. translator must be used an alternative to the expensive human translation that takes time and is usually unavailable when it is needed for communicating quickly and cheaply with people with whom we do not share a common language.

Ghina Khamis and Nour Al Oneis

Evaluation of Machine Translation Tools and Human Translation in Economic Translation Ghina Khamis and Nour Al Oneis Instructor: Dr Ghada Awada Computer-Assisted Translation TRNS301 Table of Contents : Abstract……………………………………………………………1 1- Commentary………………………………………….….....2 1.1 -Test Texts……………………………………….……..2 1.2-Evaluation……………………………………………....2 1.2.1- Semantics……………………………………..2 1.2.2- Morphology……………………………….….3 1.2.3- Syntax………………………………………...4 1.2.4- Pragmatics…………………………………....5 1.2.5- Comprehension…………………………….....6 2-Recommendations…………………………………………...7 3-Conclusion……………………………………………….......8 Terminology………………………………………………………9 References………………………………………………………..13 Abstract : In their evaluation of Human Translation and Machine Translation, Nour Al Oneis and Ghina Khamis (2013) studied and compared the differences between human’s and machine’s translation, defining the nature of translation and standards and criteria on which it is based, studying semantics, syntax, pragmatics, morphology and comprehension. This study aims to compare the effectiveness of the popular machine translation system (Google Translate) used to translate English sentences into Arabic relative to the effectiveness of English to Arabic human translation. This study will show that the Human Translation is better than Google machine translation system in terms of precision of translation from English to Arabic. This paper is set out to study the accuracy of this believe. 1-Commentary: 1.1 Test texts We performed the evaluation on two economical texts of the writer Alan Blanchette, the first entitled “Tax Avoidance” and the second “Money Laundering” , both published in 2010 and which has been reserved for testing. The texts have 504-636 words. All examples from the two texts are illustrated in that evaluation. 1.2- Evaluation: 1.2.1- Semantics: Semantic roles can determine how to properly express information in another language. Regarding the study of the meaning of linguistic expressions, it’s noteworthy to mention that many expressions and words differ in meaning between the human translation and the machine translation. Example: English العربية Human Machine catch مسك قبض Involves تشمل تتضمن wire transfers تحويلات برقية تحويلت سلكية changing the money's currency تغيير وضع العملة النقدية تغيير عملة النقود Layering involves sending the money التصنيف يتضمن ارسال الاموال التصفيف ينطوي على إرسال الأموال make it difficult to follow مما يجعل صعوبة في متابعته تجعل من الصعب متابعة But there were also similarities in the meaning in the two Translations, and it marked a kind of accuracy, and an example of this: Similarities English العربية Global financial markets الاسواق المالية العالمية Money laundering غسيل الاموال Bank-secrecy law قوانين السرية المصرفية Single scheme مخطط واحد Authorities سلطات Criminals مجرمون Embezzlers مختلسون High-value transactions معاملات ذات قيمة عالية High-value items سلع عالية القيمة The main stream economy التيار الرئيسي للاقتصاد Bank-reporting laws قوانين الابلاغ المصرفية foil money-laundering operations. احباط عمليات غسيل الاموال Drug traffickers مهربو المخدرات Financial transactions معاملات مالية Illegal money اموال غير شرعية 1.2.2- Morphology: Concerning the morphology, machine translation was ambiguous in handling word forms, achieving Number and Gender agreement, Identifying the case ending of words, and in the proper handling of pronouns, while human translation has proved its efficiency in giving the exact verb tense number, possession, and the proper gender agreement and comparison. For example, the following sentences show Morphological issues with agglutinative, fusion and complex word structure: Source Sentence: Banks usually lend money to persons who need it, for a specified interest. Google Translate: البنوك عادة إقراض المال إلى الأشخاص الذين يحتاجون إليها، لمصلحة معينة Human Translation : تقوم البنوك باعطاء القروض عادة للأشخاص الذين يحتاجون إليها، في مصلحة معينة At this stage we have to compare the outputs of Google Translate system with the Human Translation. In the first comparison we found that there is: البنوك“ Banks" الذيwho” and “يحتاجون need” are common with human translation but “إقراض المال” and “اعطاء القروض” differs. Source Sentence: The temporary closure of international banks because of the earthquake I Japan, also dented profits. Human translation: وتسبّب الزلزال المدمر الذي ضرب اليابان بالإقفال المؤقت للبنوك الدولية ، الأمر الذي أدّى إلى انخفاض هذه الأرباح Machine translation: إغلاق مؤقت ل بنوك دولي بسبب الزلزال أنا اليابان ، تراجع أيضا الأرباح. Source Sentence: Investors remain cautiously optimistic. Machine translation: ولكن لا يزال المستثمرون متفائلون بحذر . Human translation: إلا أن المستثمرين بقيوا متفائلبن بحذر 1.2.3- Syntax: Concerning syntax, a big difference in the combination of words appears, especially in dealing with Superlative Adjectives, and arranging Nouns and Adjectives and generating Nominal Chunks, hence, the human Translation syntax study is more accurate and follows the grammatical rules: Subject –Verb and we can also notice the proper use of words such determiner, modifier, complement. In the machine Translation a majority of phrases started with the verb or the verb phrase instead of the Noun, and the structure is most likely similar to the combination of words in the Arabic language, hence, the Arabic uses the: Verb – Subject – Object combinational structure while, in the English language, its : Subject-Verb + prepositional phrase. Phrase: NG (noun group), AdjG (adjective group), AdvG (adverb group), PG (prepositional group), PossG (possessive group). -In machine translation, the phrase started with a verb then subject: قد تتكون طبقات من عدة بنوك إلى بنك التحويلات - The usage of prepositions that differs in meaning, but not in structure: ومخطط واحد عادة ما ينطوي على تحويل الأموال من خلال العديد من البلدان- - والسبب في أنه من ضروري - الذي يغسل الأموال وكيف تفعل ذلك 3- the substitution of the preposition, but the reservation of the same structure and the same meaning :مما يجعل من الممكن إيداع مجهول الأموال "القذرة So the syntactic transfer rules that map parse tree for one language into one for another are: – English to Arabic: • NP → Adj Nom Þ NP → Nom ADJ • VP → V NP Þ VP → NP V • PP → P NP Þ PP → NP P 1.2.4- Pragmatics and Comprehension: Concerning Comprehension, the translation must transfer the meaning intended, which makes the comprehension part a major one. Yet, in machine translation, it is not always the case, it produces sometimes sentences, that unfortunately mean something different from the original source text. The majority of machine translation expressions have resulted into a literal and meaningless translation of the saying. For instance, the English say “A good workman is known by his chips”; which has the Arabic meaning as was literally mistranslated into “ومن المعروف ان العامل الجيد من قبل رقائقه”, by the Google translation; which is very literal and very far from the actual meaning of the saying. Source Sentence: The rise of global financial markets makes money laundering easier than ever. Machine Translation : صعود الأسواق المالية العالمية يجعل غسل الأموال أسهل من أي وقت مضى Human Translation : ارتفاع الاسواق العالمية يجعل غسل الاموال اسهل بكثير Source Sentence: In this article, we'll learn exactly what money laundering is and why it's necessary. Machine Translation: في هذه المقالة، وسوف تتعلم بالضبط ما هو غسيل الأموال والسبب في أنه من الضروري، الذي يغسل الأموال وكيف تفعل ذلك Human Translation: في هذه المقالة, سوف تتعلم بالتحديد ما هو غسيل الاموال و ما السبب في انه ضروري Source Sentence: At this stage, the launderer inserts the dirty money into a legitimate financial institution. Machine Translation : في هذه المرحلة، وغاسلي الأموال القذرة يدرج في مؤسسة مالية مشروعة. Human Translation : في هذه المرحلة, يضع غاسلوا الاموال اموالهم في مؤسسة مالية مشروعة Source Sentence: At the integration stage, the money re-enters the mainstream economy in legitimate-looking form. Machine Translation: في مرحلة التكامل، وإعادة الأموال يدخل-التيار الرئيسي للاقتصاد في شكل المشروعة المظهر Human Translation: في مرحلة التكامل, يتم اعادة ادخال الاموال للتيار الرئيسي للاقتصاد في شكل شرعي. According to these examples, we can discern the following differences in meanings: Differences English العربية Human Machine easier than ever اسهل بكثير أسهل من أي وقت the launderer inserts the dirty money , يضع غاسلوا الاموال اموالهم غاسلي الأموال القذرة يدرج the money re-enters , يتم اعادة ادخال الاموال وإعادة الأموال يدخل Hit تلقت تعرضت in legitimate-looking form في شكل شرعي. في شكل المشروعة المظهر We have found out that the overall translation precision for Google was 31,4% , if we considered that the total of words in the two articles is approximately 600 words (504-636 words), and that 188.4 words/ expressions/ morphemes were considered as inaccurate, So the degree of accuracy of the Machine Translation from English to Arabic is around 30%. 2- Recommendations: -It is necessary to improve Machine Translation either, by developing more sophisticated methods or by imposing certain restrictions on the input in order to get a good translation that is fluent, grammatically well structured and readable in the target language. - The translation machine systems (Google, Babylon, tarjim..) should be guiding International economics and should guarantee the fidel translation of documents for businesspeople, bankers, financier and other professionals. - It’s recommended improve new developed features for Translation machines, such as automatic multilingual dictionaries, that handle more support of basic research in computational linguistics. - It is necessary to provide Global Translation service for economic translation of the different types of documents (Accounting statements, balance sheets, auditor’s repots and economis statistics), and this through developed software that are specific to this domain - A Global translation service should provide high-quality translation for any information contained in economic articles, getting it across to the target audience, by including specialized terminology and a good numbering. (statistics sheet) 3-Conclusion: To sum up, English-to-Arabic machine translation has been a challenging research issue for many of the researchers in the field of Arabic Language Processing. In this study, we have concluded that the effectiveness of Machine Translation is limited, furthermore, human translation remains the most accurate and effective in translating technical texts that are related to different domain, as the economic domain . And the human Translation will always be distinct, to an important degree, from the ways in which the major Online Translating Machines as Google Translate, babyllon, etc.. translate a source text in a certain specific domain.. The human translation hence, stays in the first raw in being indispensable for translating data.

Inaam Kuteish and Maha Atwe

Abstract: In line with Inaam Kuteish and Maha Atwe (2013) This paper presents the differences between machine translation and human translation in the literary field. Literary translations are uniquely challenging because they require high-level understanding of specific terms in both the source and target language. In this paper we will tackle semantics, syntax, morphology, comprehensive and terminological differences. Also, we will shed the light on the ways of translating such documents and will show examples differentiating between translated documents. Recommendations are also given in this paper. Sample The Raven by Edgar Allan Poe Once upon a midnight dreary, while I pondered, weak and weary, Over many a quaint and curious volume of forgotten lore, While I nodded, nearly napping, suddenly there came a tapping, As of someone gently rapping, rapping at my chamber door. "'Tis some visitor," I muttered, "tapping at my chamber door - Only this, and nothing more." Ah, distinctly I remember it was in the bleak December, And each separate dying ember wrought its ghost upon the floor. Eagerly I wished the morrow; - vainly I had sought to borrow From my books surcease of sorrow - sorrow for the lost Lenore - For the rare and radiant maiden whom the angels name Lenore - Nameless here for evermore. And the silken sad uncertain rustling of each purple curtain Thrilled me - filled me with fantastic terrors never felt before; So that now, to still the beating of my heart, I stood repeating, "'Tis some visitor entreating entrance at my chamber door - Some late visitor entreating entrance at my chamber door; - This it is, and nothing more." Human translation الغراب شعر: أدغار ألن بو ترجمة: د. إنعام الهاشمي -------------------------------- - 1 - في ليلةٍ مقفرةٍ عند منتصف الليل ، حيث كنت أتأمل وأفكِّر، حائراً، متعباً وضجِر مررتُ بعديدٍ من المعتقداتِ القديمةِ الغريبة – التي غطاها ألنسيان وعندما سقط رأسي على صدري وأوشكتُ أن أغفو فجأةً جاءَ الطرقُ وكأن أحداً برفقٍ يقرعُ .. يقرعُ على بابِ مخدعي تمتمتُ "هو زائرٌ" "هو زائرٌ يقرعُ على بابِ مخدعي – هذا فقط... لا غير" ............................ - 2 - آه.. أتذكّرُ بوضوحٍ إنه ديسمبر الكثيب وفيه كلُّّ جذوةٍ تحتضرُ وتلقي بشبحِها يتمطّى فوقَ الأرض . بلهفةًٍ تمنيتُ الغد؛ – وبعبثٍ حاولتُ أن االتمسَ في كتُبي نهايةًً لهذا الأسى – ألأسى لفقدِ لينور – لتلك الفتاةِ الرائعةِ المتألقة التي أسمتها الملائكةُُ لينور – وهنا لا اسمَ لها ، ابداً بعد اليوم. ................... - 3 - الحفيفُ الحريريُّ الحزينُ والغامضُ لكلِّ ستارةٍ أرجوانية أثارني – ملأني برعبٍ غريب لم أعرفهُ أبدا من قبل ؛ والآن ، لأُهدِّئ دقاتِ قلبي ، وقفتُ أردِّد "هو أحدُ الزوّارِ يرجو الدخولَ في بابِ مخدعي "؛ – هو أحدُ زوّارِالليلِِ يرجو الدخولَ في بابِ مخدعي – هذا هو ، لا غير. Machine translation مرة واحدة عند منتصف الليل الكئيب، وأنا فكرت وضعيفة وأنهكته، أكثر من وحدة تخزين العديد غريبة وغريبة من العلم النسيان، بينما كنت ضربة رأس، القيلولة تقريبا، فجأة هناك جاء التنصت، اعتبارا من بعض واحد موسيقى الراب بلطف، موسيقى الراب في باب حجرتي. "'تيس بعض الزوار،" I تمتم "التنصت على باب حجرتي - هذا فقط، ولا شيء أكثر من ذلك. " آه، بوضوح تذكرت، أنه كان في ديسمبر القابض، ويحدثه كل جذوة مفصولة ميتة شكلت شبحا لها على الأرض. بلهفة تمنيت الغد، - عبثا التمست لاقتراض من surcease كتبي من الحزن - الحزن لفقدان ينور - لالبتول النادرة المتألقة النادرة الذين لينور اسم الملائكة - المجهولون هنا إلى الأبد. وحريري سرقة مؤكد حزينة لكل ستار ارجواني بسعادة غامرة لي - ملأني الرعب رائعة لم أحسها من قبل؛ بحيث الآن، لا يزال لضرب من قلبي، وقفت تكرار، "'تيس بعض الزوار تناشد مدخل عند باب حجرتي - بعض الزوار في وقت متأخر يستجدي مدخل عند باب حجرتي، - هذا هو عليه، وأكثر من ذلك لا شيء. " The article will tackle first Semantics: The word choice in machine translation is very weak where as the human translation which possesses an excellent word choice e.g.: "rapping at my chamber door" " يقرع على باب مخدعي"H.T: "موسيقى الراب في باب حجرتي "M.T: e.g.: "master" "سيد" H.T: "ماجستير"M.T: e.g.: "To the One in Paradise" "الى التي في الفردوس":H.T "الى واحد في الجنة"M.T: e.g.: Fluttering and dancing in the breeze H.T: تراقصُ النسيمَ وتناغي الوتر التصفيق والرقص في النسيم:M.T e.g.: unpurpeled الارجوانية H.T: M.T: unpurpled Syntax: The word order in machine translation is unorganized whereas the word order in human translation is well-organized. e.g.: "He wailed" H.T: "فرد متأسيا" M.T: "ناح انه" e.g.:This it is, and nothing more." H.T: هذا هو ، لا غير. M.T: هذا هو عليه، وأكثر من ذلك لا شيء. " e.g.: "'Tis some visitor," H.T: هو زائرٌ M.T: "'تيس بعض الزوار Morphology: Machine translation has weak grammar unlike human translation. ا E.g.: ", When all at once I saw a crowd" H.T:"فجأة وجدتُ جماعة" M.T:"في كل مرة عندما رأيت الحشد" E.g.: While I nodded, nearly napping, suddenly there came a tapping H.T: وعندما سقط رأسي على صدري وأوشكتُ أن أغفو فجأةً جاءَ الطرقُ M.T: بينما كنت ضربة رأس، القيلولة تقريبا، فجأة هناك جاء التنصت Comprehension: The comprehension level of machine translation is very low unlike the human translation. e.g.: "hon'ring" dids't"" "sent'st" "o'er" "upstarting" Quoth" H.T.: "تكريما اليك" " لم تفعلي" "ارجعته" " فوق" "منتفضاً" "قال " M.T: no translation was given e.g: surcease H.T.: نهايةً M.T: surcease Compatibility: The human translation is 90% compatible with the original text whereas the machine translation is 50% compatible. Analysis From here, we can find that the human translation is different than the machine translation; for the human translator has a mind and can comprehend and know how to make his article coherent and free of errors. The machine translated documents in the literary field are incoherent and lack the sense of comprehension and grammatical coherence. There are many differences between human translation and machine translation, in which errors regarding morphology, syntax, semantics, mechanics, coherence and comprehension are being found. The word choice in machine translation is very weak and the meaning is sometimes vague unlike the human translation which possesses an excellent word choice and uses exact terms that makes the meaning clear. The word order in machine translation is unorganized which makes the sentence barely readable whereas in human translation the word order is well-organized which makes the sentence very clear. Moreover, machine translation has weak grammar such as in sentence structure. . So in machine translation a lot of grammar mistakes are made while a human translator avoids the grammatical mistakes. The comprehension level of machine translation is very low because the machine translation doesn't comprehend the figurative language and the culture especially when it comes to proverbs and sayings unlike human translation. In addition, machine translation is unable to comprehend the old English language like the human translator. In human translation the original text is 90% compatible with the target text whereas in machine translation it is 50% compatible, the text might be explicable but barely readable. Recommendation It is imperative for translators to refrain from using machine translation. In case translators were obliged to seek help they can refer to specialized dictionaries, in addition we recommended to use tradius Moreover, if machine translation is used one should revise the whole text and check the mistakes. It is recommended for those who want to translate texts to seek translators and not machines because a translator can render the original text in an effective and clear way unlike the machine. Although some decoys can be found in the machine translated documents because of the structural changes, these are no more than 5% of the whole document, hence here comes the role of the human translator to detect the errors and correct them. Conclusion To sum up, machine translation has many disadvantages. Machine translation is not reliable; it doesn't give exact meanings, its word order is unorganized, it is weak in structure, it makes many grammar mistakes, and it lacks the ability to comprehend the whole text unlike a human translator who lacks all of these problems. To avoid these problems one should simply resort to human translation. But whenever the translator do his job in a way using his translating skills with the help of the machine, his job will be achieved perfectly without any errors or changes in the meaning. References Hashmy,I. (2011) . The raven. Retrieved on November 24, 2012 from http://www.almothaqaf.com/index.php?option=com_content&view=article&id=6529:2009-10-17-13-32-20&catid=35:2009-05-21-01-46-04&Itemid=0 Hashmy, I.(2011). The raven. Retrieved on July 20,2012 from http://www.babylon-center.net/?articles=topic&topic=556

Reem Bazzal, and Maha Atwi

Abstract In their text Machine Translation System and Human Translation with economic texts (2013), Reem Bazzal, and Maha Atwi intend to discuss the proper use of available online machine translation technologies in economic translation and provide an objective view of the suitability and reliability ofthese systems in translation. To illustrate more, practical texts have been submitted and they were translated by both Machine Translation and Human Translation. The evaluation ofthe work of such technologies and of human translation came based to four different aspects: semantics, syntax, morphology and comprehension and they concluded that although Machine translation results are not that reliable, they can help in producing a well understood text and help in finding some terms and expressions related to the economic field. This paper is set out to verify this belief. Commentary For a fair comparison of the performance of different online MT systems and Human Translation on economic texts, they needed appropriate texts that the MT systems can evaluate. The texts they chose Money Laundering is made up of 406 words in its English version and the other text Difference between Tax avoidance and Tax Evasion is made up of 243 words in its English version. They are therefore a reliable test set for examining the translation quality of economic texts by MT systems and human translation and to produce substantial statistical analysis for their performance in quantitative evaluation. After translating the two texts by a human translation and machine translation which is google translate, we concluded the following: Semantics: When it comes to semantics, the meaning or the interpretation of a word or sentence we noticed that there are differences and similarities between the human translation and the machine translation. For example, the human translation in the text money laundering translated the word: wire transfer as تحويلات برقية while the machine translated it as تحويلات سلكية . The word catch in human translation meant مسك while in machine translation it meant قبض. The phrase changing the money’s currency was translated in human translation to تغيير وضع العملة النقدية while in machine translation it was translated to تغيير عملة النقود . Despite the differences, machine translation and human translation had some words and expressions that hold the same meaning. For example, Global financial markets الاسواقالماليةالعالمية/ Money laundering غسيلالاموال/Bank-secrecy law قوانينالسريةالمصرفية/ Bank-reporting laws قوانينالابلاغالمصرفية. Morphology: Concerning the morphology, machine translation has a problem when it comes to translation related to Inflectional morphemes, the exact number, gender of the subject and the exact verb. When translating from Arabic to English, the agreement between grammatically linked items was often missing which led to some sentences that can be hardly understood. While human translation has proved its efficiency in giving the exact verb tense number, possession, and comparison. Source Sentence: The temporary closure of international banks because of the earthquake I Japan, also dented profits. Human translation: وتسبّبالزلزالالمدمرالذيضرباليابانبالإقفالالمؤقتللبنوكالدولية،الأمرالذيأدّىإلىانخفاضهذهالأرباح Machine translation: إغلاقمؤقتلبنوكدوليبسببالزلزالأنااليابان،تراجعأيضاالأرباح. Source Sentence: Investors remain cautiously optimistic. Machine translation: ولكنلايزالالمستثمرونمتفائلونبحذر . Human translation: إلاأنالمستثمرينبقيوامتفائلبنبحذر Syntax: Concerning the word order (syntax): the human translation is better than machine translation. The word combination in human translation is respected and well organized. It is more accurate and follows the grammatical rules: subject-verb and we can also notice the proper use of words such determiners, modifiers, and complements While in machine translation a majority of phrases started with the verb or the verb phrase instead of the noun, and the structure is most likely similar to the combination of words in the Arabic language, hence, the Arabic uses the : verb-subject-object combinational structure while in the English language, it is subject-verb-object- prepositional phrase (noun group, adjective, adverb ,prepositional, and possessive) so it’s obvious that google translate was unable to give good results for example: Comprehension: After comparing the two methods of translation we noticed that the target texts in the machine translation and despite the mistakes can be understood. But the use of grammar and punctuation is not correct and the sentences are sometimes lengthy and complex. Also, MT produces some sentences that are unfortunately far from the meaning given in the source text. As for human translation, the texts we well understood, the meaning was clearly stated in the target language and the use of grammar and punctuation is correct. Take the following sentences as examples: Source Sentence: The rise of global financial markets makes money laundering easier than ever. Machine Translation : صعودالأسواقالماليةالعالميةيجعلغسلالأموالأسهلمنأيوقتمضى Human Translation : ارتفاعالاسواقالعالميةيجعلغسلالاموالاسهلبكثير Source Sentence: At the integration stage, the money re-enters the mainstream economy in legitimate-looking form. Machine Translation: فيمرحلةالتكامل،وإعادةالأمواليدخل-التيارالرئيسيللاقتصادفيشكلالمشروعةالمظهر Human Translation: فيمرحلةالتكامل, يتماعادةادخالالاموالللتيارالرئيسيللاقتصادفيشكلشرعي. Recommendations: It is important to understand that machine translation is an interesting field of research but it is not a substitute for a professional translation produced by a human translator who is able to give exact meanings of the terms and expressions used. It is necessary to develop the machine translation that are related to specific domains so that terms related to economic or legal can be easily conducted and used. It is preferable to add translation memories to all machine translation to make sure that terms used are saved for the purpose of using it in the translation of other texts that are related to the same domain. It is necessary to improve the ability of the machine translation in focusing more on the production of perfect economic texts not only on the comprehension side. It is important to develop new machine translation methods that can help in creating well grammar links and understood sentences.