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Sunday, November 10, 2013

Can Machine Translation make professional translation?


Machine Translation usually refers to the use of computers and software for the translation of a text/message from one language to another. 

In its beginnings in the 1950s, machine translation relied on the substitution of words in the target language.  But, since this led to strange constructions and failed to look like a natural language, machine translation relied on corpus and statistics.  One of the main problems is the differences in language typologies.  Languages from two different families present more difficulties to machine translation attempts. 

However, the use of substitutions is still in place.  One way to make this substitution less risky is to use sensors or identifiers of the lexical field in question.  If the text talks about a kitchen description, for example, the word ‘sink’ is translated appropriately into Arabic, rather than using a word which refers to drowning in the sea/water pool.  Of course, a professional Arabic translator won’t need a lexical categorization in order to identify which term is meant!

By relying on human intervention, machine translation can be made more accurate and reliable.  The identification of the word class of some problematic words makes it easier for the output to be less confusing.  Some Arabic names are translated into nouns and adjectives, and this makes the output more confusing.

Moving from being a mere illusion to some practical achievements has made Machine Translation more feasible and acceptable for users.   People claim that the product of Machine Translation can be safely used in some domains.  But, if the frequency of error is important and if the possibility that errors can happen, the reliability level remains very limited, especially in scientific, legal and technical domains.

However, the achievement of a totally professional output seems more difficult than realistic.   It remains reasonable to think of MT as a tool any users can apply in order to get the gist of a text, especially when the source and target languages are from the same language family.  Accuracy and professionalism require going beyond the mere replacement of words to the artistic, stylistic and skillful linguistic formulation of a message in another language.  Style and language-specific nuances are not easily achieved by human translators, not to mention the limitations of computer software.  Hence, these limitations remain inherent in all MT applications.  This applies to literary texts, normal interactions in everyday language as well as to texts in humanities and social sciences.  Although automated translation has shown promising results, prospects seem very limited since the integration of an experienced smart individual with a native communicative competence into software is far from being achievable.  

One more issue is that human translation goes through a quality assurance process.  Every translation needs double checking and an external proofreading in order to be professional and reliable.  However, MT cannot meet these quality requirements.   In fact, sending machine translations to proofreaders to check, apart from aiming at reduce the cost at the expense of the translator’s profit, reveals that translation is an human art, and not an aspect of automation. 
     
It is worth mentioning here that CAT tools are different from machine translation (MT).  Computer Aided Translation aim at helping human translators make perfect translations with more output and consistent terminology.  Professional translators need them to improve their daily output and employ the same terms in the whole document. 
    
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