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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.
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]
The translation of multimedia creative works is a subject of academic research, a subtopic of translation studies. [5] This interdisciplinary field draws from a wide range of theories, such as globalisation and post-globalisation theories, reception studies, relevance theory, social science and cultural studies, social psychology and deaf ...
He estimates that the theory and practice of English-language translation had been dominated by submission, by fluent domestication. He strictly criticized the translators who in order to minimize the foreignness of the target text reduce the foreign cultural norms to target-language cultural values.
The following table compares the number of languages which the following machine translation programs can translate between. (Moses and Moses for Mere Mortals allow you to train translation models for any language pair, though collections of translated texts (parallel corpus) need to be provided by the user.
In translation studies, the accepted meaning is now as a new translation into the same target language of a previously translated work. [6] The traditional conceptualization holds that the process is linear [ 7 ] or chronological, with retranslation always taking place after the first translation. [ 8 ]
Example-based machine translation (EBMT) is a method of machine translation often characterized by its use of a bilingual corpus with parallel texts as its main knowledge base at run-time. It is essentially a translation by analogy and can be viewed as an implementation of a case-based reasoning approach to machine learning .
Literal translation, direct translation, or word-for-word translation is the translation of a text done by translating each word separately without analysing how the words are used together in a phrase or sentence. [1] In translation theory, another term for literal translation is metaphrase (as opposed to paraphrase for an analogous translation).