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In semantics, the best-known types of semantic equivalence are dynamic equivalence and formal equivalence (two terms coined by Eugene Nida), which employ translation approaches that focus, respectively, on conveying the meaning of the source text; and that lend greater importance to preserving, in the translation, the literal structure of the source text.
Untranslatability is the property of text or speech for which no equivalent can be found when translated into another (given) language. A text that is considered to be untranslatable is considered a lacuna, or lexical gap. The term arises when describing the difficulty of achieving the so-called perfect 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 ...
According to Lawrence Venuti, every translator should look at the translation process through the prism of culture which refracts the source language cultural norms and it is the translator’s task to convey them, preserving their meaning and their foreignness, to the target-language text. Every step in the translation process—from the ...
You can choose one of these templates that tag text with inline messages to request specific clarifications that you cannot provide yourself: {{ Clarify }} to mark individual phrases or sentences {{ Confusing }} to mark sections (or entire articles, though this is undesirable because it makes it unclear what exactly needs to be improved)
The term Multilingual Information Retrieval (MLIR) involves the study of systems that accept queries for information in various languages and return objects (text, and other media) of various languages, translated into the user's language.
Collaborative translation [53] can also contribute to translanguaging because many participants can translate simultaneously in the same document. This technique is fundamental because learners can utilize all the language knowledge, they have from their first, second or third language to input and expand knowledge in several areas.
Machine translation is use of computational techniques to translate text or speech from one language to another, including the contextual, idiomatic and pragmatic nuances of both languages. Early approaches were mostly rule-based or statistical. These methods have since been superseded by neural machine translation [1] and large language models ...