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The origins of machine translation can be traced back to the work of Al-Kindi, a ninth-century Arabic cryptographer who developed techniques for systemic language translation, including cryptanalysis, frequency analysis, and probability and statistics, which are used in modern machine translation. [3]
Translation studies is an academic interdiscipline dealing with the systematic study of the theory, description and application of translation, interpreting, and localization. As an interdiscipline, translation studies borrows much from the various fields of study that support translation.
A rendition of the Vauquois triangle, illustrating the various approaches to the design of machine translation systems.. The direct, transfer-based machine translation and interlingual machine translation methods of machine translation all belong to RBMT but differ in the depth of analysis of the source language and the extent to which they attempt to reach a language-independent ...
His most important contribution is in comparative literary studies and translation studies in particular. Drawing upon the notions of polysystem theorists like Itamar Even-Zohar , he theorized translation as a form of rewriting produced and read with a set of ideological and political constraints within the target language cultural system.
Emily Wilson, a professor of classical studies at the University of Pennsylvania and herself a translator, writes: "[I]t is [hard] to produce a good literary translation. This is certainly true of translations of ancient Greek and Roman texts, but it is also true of literary translation in general: it is very difficult. Most readers of foreign ...
Machine translation is a sub-field of computational linguistics that investigates the use of software to translate text or speech from one natural language to another. In the 1950s, machine translation became a reality in research, although references to the subject can be found as early as the 17th century.
Rule-based machine translation (RBMT; "Classical Approach" of MT) is machine translation systems based on linguistic information about source and target languages basically retrieved from (unilingual, bilingual or multilingual) dictionaries and grammars covering the main semantic, morphological, and syntactic regularities of each language respectively.
The idea behind statistical machine translation comes from information theory.A document is translated according to the probability distribution (|) that a string in the target language (for example, English) is the translation of a string in the source language (for example, French).