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Arabic Languages: Contributions and Limitations

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Arabic Languages: Contributions and Limitations 6 IJCSNS International Journal of Computer Science and Network Security, VOL.19 No.7, July 2019 A survey on Bi-Directional Machine translation (MT) approaches of English/ Arabic Languages: Contributions and Limitations Insaf Ali Simming1, Nasreen Nizamani2, Rubina Shaheen3, Ali Siddiqui4, Agha Kousar5 1,5Quaid-e-Awam University of Engineering, Science and Technology (QUEST), Nawabshah, Sindh, Pakistan 2Department of Electronic Engineering Quaid-e-Awam University of Engineering, Science and Technology (QUEST), Nawabshah, Sindh, Pakistan 3Shah Abdul Latif University, Khairpur, Sindh, Pakistan 4English Language Development Center (ELDC), Mehran University of Engineering and Technology (MUET), Jamshoro, Sindh, Pakistan Abstract second language (that is to be translated). The definition by Present work sketches a brief historic perspective of Machine Systran, (2004) have tended in emphasis about machine Translation (MT) application within natural languages. It explores translation that can be stated of not only changing words different types of translation approaches. Therefore, to with the other words but also involves the human comprehend the application of Machine Translation practically, translation that includes system of complicate rules of Arabic and English languages were for study. However, the linguistics. It evolves within semantics, syntax and to a relation of translation between Arabic and English languages is dated back to early its eras of 1950s in USA. The history of small unit of morphology. The definition states “The machine translation has witnessed a continuous flux of successes European Association for Machine Translation” have and fails. After 1980s, the situation of translating English to highlighted: “an application that has work to translate any Arabic languages experienced a remarkable era. Many of the text of natural language into other. It is one of the early achievements have been witnessed through various contributions researches within field of IT Science that not only prove in from different academic disciplines. This paper has briefly stated handling this but now many of the other systems are present about the contributions made in domains of constructive that could make an output. It can be made useful within translation models, machine translation systems and computer many of different fields” European Association for software. It further explores about the true resources of online Machine Translation in 2004. Definition by Doug Arnold translation assistance for natural languages in shape of online and manual dictionaries as a practical representation to a conceptual et al. (1994), has mainly defined to affirm many definitions. framework of translation models that promotes its functionality One of the prominent definition is as “Machine Translation worldwide. The significance of present study lies within a fact that is an attempt to automatically or as a part for the entire it explicitly shows a hierarchal lineage of both languages taken as process to translate a text that is into one human language a sample of study. Secondly, the lingual characteristics of English to the other.” and Arabic languages compared to each other that connect application with some challenges that are raised because of their 1.1.1 View on the Historic Accounts striking contrasts. However, it gives an impetus for future researchers from various disciplines to explore many subtle The authority on Machine Translation, named W. John paradigms within their respective subjects. Hutchins (1995) has significantly researched about various Key words: marked traces about Machine Translation, recorded back to Lingual Characteristics, historic perspectives, Arabic, English, 17th century. Peter Smirnov-Troyanskii of Russia, 1937 MT contributions has enunciated three constructive stages for editing the mechanical machine translations. 1. Introduction 1.1.2 Pinnacle of Age 1.1 Translation in Machines: Definition and There was a great issue on acknowledging the limits to perspectives simple dictionary systems that used to develop approaches for analyzing source texts within stated grammatical It is described as a “process that accomplices software of regulations. In this respect, The Economist (2002) has cited computer in order to convert text of one language to other” in Atlantic Monthly of 1959 by stating as: “For now, Systran (2004). Therefore, it possesses the work into computer systems, or even of the electronic brains are grammar structure of natural language according to set efficient enough towards conceiving load of application regulations along with some assumptions for transferring known to be as machine translation.” However, this structural grammar of First language (source text) into Manuscript received July 5, 2019 Manuscript revised July 20, 2019 IJCSNS International Journal of Computer Science and Network Security, VOL.19 No.7, July 2019 7 optimism later seemed as “disillusion” within mid-year to Lack of a rule to combine two letters for creating an other Two letters does combine to 1960s. Even though responsible government sponsors have sound. (th sound is reduced create another sound. (th in (in Arabic (Salem et thinking , sh in sheep ( ث utilized MT within US formed broad committee in order to into al.,2008) evaluate and examine about overall field. With this, No “copula verb- to be”. This Automatic Processing Advisory Committee (ALPAC) later results in unique usage of Presence of “copula verb- to be It is of (is, was, etc.) The sky is clear (The way it السماء) (have presented renowned points to 1966 by highlighting subject “I” (GOOGLE The Sky clear = ( صافية Machine translation as less effective, slower and more (Literal) should) There is gender expensive than human translation. Further, the report even There is only differentiation between male and female differentiation between tried to state that there is no benefit of investment within female, male and neutral. within verbs and nouns. Verb form does not field of MT research. Within 1980s, even Hutchins (1995) It lacks neuter gender marks of Japan to have maintained the greatest of all demarcate the genders. It has irregular, flexible word commercial activities for almost different computer agreement and Order. It has a regular word order companies as Japanese into English translation system. The Examples: (VOS), (SVO), arrangement. (OVS) and (VSO) Commonly history of Och’s work (Makin 2003) has stated that it was observed arrangements: The word order is SVO. an improvement within earlier stated achievements onto (VSO) and (SVO) Words usually change their The quality of changing the statistical approaches started back in late 1980s. It shape with respect to their position. They are either in shape of word is present in continued within early phases of 1990s contributed to Arabic language. (Peter F. Brown et al.,) and IBM’s Watson Research Center start, middle or in the end. It has number representation (WRC). The document of Interpretation and Translation of a subject (2004) also accounts to best example of Meteo system and object in terms of It has number representation singular, plural and dual form. of a subject and object in emerged within Montreal of translate to Canadian News It has two numbering systems. terms of either singular or Bulletins to English into French, vice-verse. It was based One that was learnt from plural. Indians and other is the on daily transmission that dates back in 1977. Machine original one. translations have beneficial impact within many fields that An agreement is found as a No any type of agreement is opened new projects within this scenario. (AAAI, 2005) requirement of adjectives to be found between subject and its in with number, case, gender predicative adjective that have reported number of many related innovated and definitiveness with noun. shall be a number or the .gender البيت اﻷحمر contributions. (Red House) and (Red houses) Number: Red house (Sing) (GOOGLE) البيوت الحمراء The sentence is either nominal The sentence is always 2. The Case of Arabic Language for Machine or verbal nominal It possesses three cases It possess nominative, Translation (Nominative, genitive and genitive , accusative and accusative) Dative. (four cases) The form of tenses that 2.1 Comparison of Linguistic Features Within Arabic Form to tenses that represent represent same action in same action in different time and English Languages framework is derived from different time framework can many times represent words one specific root. Example: of different origin. present) Went) (الذهاب) Arabic English Go (past) Example: Go (present form) (ذهب ) West Germanic language of Went (Past form) Semitic Language the Indo Presence and absence of “al- European Origin Taskeel” One of the major Six Set as a first choice of foreign diacritics does alter meaning English language lacks such Languages language(Lingua Franca) of the word. quality ( لطيفة ) = Two forms: Varieties of English (World Example: Nice ( لطيف ) = Modern Standard-Arabic Englishes) (GOOGLE) Gentle (MSA) American English and British It has some words that Dialectic-Arabic (DA) English themselves represent Letters = 28 Letters = 24 ownership attribute with their Vowels = 5 use. s’ after an object usually ( يا ,و ,ألف) Vowels = 3 Aspiration marks: Sukun, Consonants = P, G, V have no Example: represents someone’s belonging. With an attribute (سيارته) = Shadda (Tashdid), Fatha, any existence in Arabic His car kasra, Damma language. (SYSTRAN) usually “of” is employed. :Example (صديق) = Writing
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