Introduction
The field of Computational Linguistics is relatively new; however, it contains several sub-areas reflecting practical applications in the field. Machine (or Automatic) Translation (MT) is one of the main components of Computational Linguistics (CL). It can be considered as an independent subject because people who work in this domain are not necessarily experts in the other domains of CL. However, what connects them is the fact that all of these subjects use computers as a tool to deal with human language. Therefore, some people call it Natural Language Processing (NLP). This paper tries to highlight MT as an essential sub-area of CL. The types and approaches of MT will be considered, and limitations discussed.
Computational Linguistics
Linguistics and Computer Science are the main components of CL. According to Bolshakov & Gelbukh (2004) CL can be defined as a synonym of NLP. CL aims to construct computer programs which are able to process (recognize and synthesize) texts and speech of natural languages. This process enables scientists to create several applications related to this field such as Machine Translation, Spell and Grammar Checkers, Information Retrieval, Speech Recognition and Speech Synthesis, Topical Summarization, Extraction of factual data from texts, Natural language interface.
A Brief History of Machine Translation
There is no doubt that scientists have paid attention to MT as one of the main computational-linguistics domains. Slocum (1984) states that the development of MT programmes started in the 1950s. The first applications such as Systran and Meteo were able to translate from one language to another word by word. The research in machine translation has developed significantly in...
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If you have ever had a conversation with someone whose first language is not the same as your own, you are probably familiar with the idea that there are certain words and phrases that do not translate perfectly from one language to another. This conflict is usually a matter of one language having a single word or succinct phrase for a concept which another language might need an entire sentence to capture.
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According to Freda (2006), Statistical Measure of Gobbledygook is among the simplest methods, which can be used to determine the reading level of any written material. Several calculations are performed without using computer programs. A sample of sentences is obtained from the start, middle, and end of the text. After w...
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For the VSO word order and partial agreement for the SVO word order. Also, Arabic
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To answer the question above we first have to define what is actually meant by translation before we are able to think about the limits and advantages of translation. Translation can be described as an expression of a sense from one language to another as well as a transmission of a written or spoken language into another.
The Importance of the Brief for a Translator under the Framework of the Skopos Theory
In human society, translation plays a significant role, which helps realize effective communication among people. Benjamin (as cited in Venuti, 2000) indicates translation is the mode, which plays a function of transmitting information; hence translatability determines whether the information could be effectively and appropriately delivered and is regarded as the “essential quality of certain works”. Throughout history, many scholars have developed translation theories, which provide various effective translation strategies and methods, to explore the translatability. Equivalence theory points out that all languages always share some similarities; hence the languages could be exchanged (Nida, as cited in Venuti, 2000). The skopos theory emphasizes
There are several theorists of translation procedures i.e translation techniques. According to Vinay and Darbelnet as cited in Walinski (2015), translation procedures can be divided into two types : direct translation and oblique translation. Direct translation can be defined as word by word translation of the target language’s original message. It involves borrowing, calque, and literal translation. Meanwhile, oblique translation is a translation procedure in which the translator interprets, e.g. elaborates or summarizes the explicit contents of the original, includes transposition, modulation, equivalence, and adaptation.
The work of the translator stars with the reading of the ST: he has to study the lexicon, the grammatical structure, the communicative intention of the writer, and of course the cultural context in which is developed the ST, in order to identify the best translation strategy able to express the original intention.
The essential problem with translation is an obvious one. A word has more qualities than just its denotation. For one, a word has a sound, an attribute which has great importance in poetry (though we should not underestimate its significance in prose, as well). Also, a word consists of various connotations, meanings which only rarely cross over from language to language. Complicating matters is the nature of literature itself. Writers and poets put pressure on the language; they often choose words because of their rich variety of meanings, complicating rather than clarifying their subjects. Unfortunately, then, for the translator of literature, the currency of words is not as easy to exchange as the other kind of currency.
As an example, in the phrase “I feel great about it, we should celebrate!” there are two main prosodic phrases with the boundary at the punctuation mark. Prosodic phrasing involves finding these types of meaningful prosodic phrases, which may or may not be explicit. Prosodic phrasing is important because it not only increases the understandability of synthesized speech but also helps ascribe meaning to certain parts of the synthesized speech, in the same way humans do, by varying prosody. This is done by creating prosodic boundaries at explicit identifiers like punctuation marks, or at certain lexical or grammatical words, known to be phrase delimiters for a language. Several researchers have tried using variants of context-free grammars like augmented transition networks (ATNs), definite-clause grammars (DCGs) and unification grammars (UGs) to model syntactic-prosodic structures in languages and use them to identify the prosodic phrases in the input text [29–31]. Another approach is to use statistical models, with probabilistic predictors like CART decision trees, to predict prosodic phrases based on features such as the parts of speech of the surrounding words, the length of an utterance in number of words, the distance of a potential boundary from the beginning or the end of an utterance and whether surrounding words are accented [32] Even though the rules based on punctuation are good predictors of prosodic phrases, there are many cases where explicit punctuation marks are not present to indicate the phrase boundaries. This problem is prominent in the case of Indian languages where there is little or no use of punctuation marks. Sridhar [33] uses an elementary deterministic rule based phrasing model for Hindi using the content/function word
The other part of computational linguistics is called applied computational linguistics which focuses on the practical outcome of modeling human language use. The methods, techniques, tools, and applications in this area are often subsumed under the term language engineering or (human language technology. The current computational linguistic systems are far from achieving human ability of communicating they have numerous applications. The goal for this is to eventually have a computer program that will have the same communication skills as a human being. Once this is achieved it will open doors never thought possible in computing. After all the major problem today with computing is communication with the computer. Today’s computers don’t really understand our language and it is very difficult to learn computer language, plus computer language doesn’t correspond to the structure of human thought.