Translation is the action of interpretation of the meaning of
a text, and subsequent production of an equivalent text, also called a
translation, that communicates the same message in another language.
The text to be translated is called the "source text," and the language
it is to be translated into is called the "target language"; the final
product is sometimes called the "target text."
Translation must take into account constraints that include context,
the rules of grammar of the two languages, their writing conventions,
and their idioms. A common misconception is that there exists a simple
"word-for-word" correspondence between any two languages, and that
translation is a straightforward mechanical process. A word-for-word
translation does not take into account context, grammar, conventions,
Translation is fraught with the
potential for "spilling over" of idioms and usages from one language
into the other, since both languages repose within the single brain of
the translator. Such spilling-over easily produces linguistic hybrids
such as "Franglais" (French-English), "Spanglish" (Spanish-English),
"Poglish" (Polish-English) and "Portunol" (Portuguese-Spanish).
The art of translation is as old as written literature. Parts of the
Sumerian Epic of Gilgamesh, among the oldest known literary works, have
been found in translations into several Asiatic languages of the second
millennium BCE. The Epic of Gilgamesh may have been read, in their own
languages, by early authors of the Bible and of the Iliad.
With the advent of computers, attempts have been made to computerize or
otherwise automate the translation of natural-language texts (machine
translation) or to use computers as an aid to translation
translation, sometimes referred to by the abbreviation MT, is a
sub-field of computational linguistics that investigates the use of
computer software to translate text or speech from one natural language
to another. At its basic level, MT performs simple substitution of
words in one natural language for words in another. Using corpus
techniques, more complex translations may be attempted, allowing for
better handling of differences in linguistic typology, phrase
recognition, and translation of idioms, as well as the isolation of
Current machine translation software
often allows for customisation by domain or profession (such as weather
reports) � improving output by limiting the scope of allowable
substitutions. This technique is particularly effective in domains
where formal or formulaic language is used. It follows then that
machine translation of government and legal documents more readily
produces usable output than conversation or less standardised text.
Improved output quality can also be achieved by human intervention: for
example, some systems are able to translate more accurately if the user
has unambiguously identified which words in the text are names. With
the assistance of these techniques, MT has proven useful as a tool to
assist human translators, and in some cases can even produce output
that can be used "as is". However, current systems are unable to
produce output of the same quality as a human translator, particularly
where the text to be translated uses casual language.