International Journal of Science and Research (IJSR) ISSN (Online): 2319-7064 Index Copernicus Value (2013): 6.14 | Impact Factor (2013): 4.438 A Linguistics Study of New Trends in Translation as a Speech to Act Riyad Sarhan Jabbar Faculty of Education, University of Kufa, Najaf, Iraq, P. O. Box 21 Abstract: Machine translation is the only available alternative to human translation. Thus, evaluating machine translation software, is very important to improve the performance of these software. This study aims to highlight the difference between human translation and machine translation with reference to speech to text program . In this study , the approaches of translation are mentioned as direct approach , interlingua approach , and the transfer approach . The problem of this program is with the literary translation more than the other types of translation as scientific and idioms . The most accurate is the scientific one as this study proves . As a solution to overcome the problem of literary translation is that machine translation software should be modified and updated continuously , so that they can keep pace with the follow of literary terms . Also , the study shows the advantages and disadvantages of using machine translation. Moreover, the work illustrates the types of linguistic problems encountered in machine translation, and some solutions to overcome these problems. Keywords: Translation, Machine Translation, Translation software, speech, Text, Transfer approach, Interlingua approach 1. Introduction 1.2 The Aims of the Study 1.1 The Problems of the Study 1) The study will attempt to come out with some solutions to machine translation (MT) problem whenever possible The mechanization of translation it has been one of so as to come with highly quality automatic translation . humanity's oldest dream . In the twentieth century it has 2) Highlighting the differences between human translation become a reality ,in the form of computer programs or and machine translation , and to prove which is the more mobile telephones capable of translating a wide variety of useful than the other. texts from one natural language to another. No machine can 3) Showing the working process of speech-to-text produce a perfect translation in any language without human translation that enable simple voice communication intervention or assistance . (Hutchins and Somers , 1992 : 5 ) across a language barrier, by using a handheld The two languages, English and Arabic are related to two mobile with a microphone to create text to , Speak, different families, so it is absolutely expected to have translate, listen, send and search using Speech to Text different points in grammar , word orders, types of Translator TTS . sentences, forms of verbs, terms, articles, adverbs, adjectives, etc. from all this, problems in any machine 1.3 The Hypothesis of the Study translation will definitely arise. (Abdulhassan,ND:1) these problems are: The hypothesis of this study are: 1) The study hypothesized that speech to text program is 1) Investigating the ability of machine translations software more useful when dealing with machines since these whether they are able to make all types of sentences on the programs are not only economical but also present a same level of efficiency or it will give one meaning shortcut for users who find it difficult to deal with the regardless other meanings. complications of new technology . 2) Showing how Google translation and the automated phone 2) Machine translation leads to mechanical speech which in operator have failed to translate abstract ideas, shift in return is not always accurate and problematic when it tone, words that means more than one thing due to the comes to rhetorical and literary texts . lack of equivalent terms and the different backgrounds of the terms. 1.4 The Procedure of the Study 3) The machine translation have failed to introduce reader with a clear idea of idioms, terms and expressions, owning The procedure of this study are : to the lack of some ( semantic, pragmatic, discourse...) 1) To assess the efficiency of (TTS) machine translation so, which collectively determine the surface structure of this study will make comparison of different kinds of target language texts, and many other features in which texts in different fields such as history text ,scientific text human translation have. However , machine translation , and literary text so as to come out with the result which software are efficient and practical means to reduce time, one is more accurate than the other. money and effort spent on translating words as well as it is 2) Makes comparison between different kinds of (MT) very easy that enable the learner to learn what ever they software application in its ability and to discover which want in any time . is better than the other. 3) In addition, investigates the terminology and idioms used in speech to text TTS programs. Volume 4 Issue 2, February 2015 www.ijsr.net Paper ID: SUB151039 Licensed Under Creative Commons Attribution CC BY 347 International Journal of Science and Research (IJSR) ISSN (Online): 2319-7064 Index Copernicus Value (2013): 6.14 | Impact Factor (2013): 4.438 هيكنة الترجوة كاى هي أقدم حلن البشرية في القرى العشريي The Limits of the Study 1.5 This work is not to be considered as a prescriptive study, and The main principle of this system was taking the words of its conclusions are not in debatable. On the contrary, the the source text one at a time, looking for their equivalents in work describes the stages of machine translation a bilingual dictionary, and then bringing them to the output developments, and the types of problems which may affect text which is, naturally, in the target language, in the same the quality of the final product of machine translation speech sequence as the source text. It may happen frequently that a TTS. Thus, the study stepped aside the discussion of other word in the source text might have more than one equivalent problems related to the evaluation of whole texts by machine or meaning, hence, the system prints all these meanings and translation specially to Speech to text . leaves the choice to the human monitor to pick the right one. For example: The word (note) when it is translated to Arabic ػ Perhapsٍّخ ٚسل١خ ِﻻزظخ, , ػٍّب : The study also avoided deeper investigation into the language give those options specifications and technical features of (MT) software, the best example of the direct (MT) system is the system of which can be regarded as more related to computers the Georgetown Automatic Translation (GAT). The main engineering rather than linguistic applications. aim behind using this system was to translate Russian physics into English. The distinct features of the system 1.6 The Value of the Study were its word-for-word translation with some local word- order adjustment. The output quality was very poor, if 1) The study in this field is intended for researchers, compared to human translation.(Slocum, 1985:4) translation teachers, translation students for the purpose This kind of system design was suitable for certain types of of education. use, but it was not adequate for other purposes. 2) This study is important because it highlights the The Georgetown (MT) project was terminated in the mid developments in (MT), the linguistic problems, and 1960s . (ibid) human factors which affect the quality of (MT) output. 3) The writers ,translators, businessmen , for people who they are unable to write so they can translate easily by speaking . Section Two 2. Machine Translation 2.1. Machine Translation Concepts Machine translation refers to the automatic production by computer or similar machine such as mobile translation now Figure 1: This Figure Shows The Direct System days the machine program must contain rules to analyze the Direct MT Systems: (Lawson,1982:24) original text in the source language and to find grammatical and lexical equivalents contained in its dictionary store , and 2.2.2 .The Interlingua Approach to synthesis anew version of the original text in the target The search for more practical approaches than the direct language .(Abdul Hameed, 1998:10). translation led to other system called interlingua in the 1960. The Interlingua approach, is based on ―the argument that Hutchins (1986: 15) defines Machine translation (MT) as MT must go beyond purely linguistic information (syntax "the application of computers in the translation of texts, and semantics) and involve an ‗understanding‘ of the content from one natural language into another language" thus , of texts‖. computers are intended to carryout any definite rules of The motivation behind devising an interlingua was the long- thumb process which could have been done by a human lived belief that languages differ greatly in their ―surface operator working in a disciplined, but an intelligent manner. structures‖, they all share a common ―deep structure‖. The electronic computer should however obtain it's results Hence, arose the idea of creating a universal representation very much more quickly. (Turing,1951:1) capable of conveying this deep structure while enjoying the regularity and predictability natural languages lack. 2.2 Machine Translation Approaches (Alnsary, N.D:1). In this type of systems the translation are of two stages 2.2.1.The Direct Approach process. From source language into the interlingua, and from In the 1950s, the general strategy employed in systems the interlingua into the target language. (Lawson, 1982: 26). design was the direct translation. (Hutchins, 1982: 22) .The As a practical application of the Interlingua system design. direct approach is mainly a lexicon-based approach in which "The Centre d'Études pour la Tradition Automatique a computer program performs a word-for-word substitution (CETA) " (Wageh ,2008:28).project was started at Grenoble with some local adjustment between language pairs using a University, France in 1961. The system was designed to large bilingual dictionary.