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, and idioms. 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 (computer-assisted translation). Machine 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 anomalies. 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.