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In translation and semantics, dynamic equivalence and formal equivalence are seen as the main approaches to translation that prioritize either the meaning or literal structure of the source text respectively. The distinction was originally articulated by Eugene Nida in the context of Bible translation.
Grammatical abbreviations are generally written in full or small caps to visually distinguish them from the translations of lexical words. For instance, capital or small-cap PAST (frequently abbreviated to PST) glosses a grammatical past-tense morpheme, while lower-case 'past' would be a literal translation of a word with that meaning.
Rules in these grammars apply to two languages at the same time, capturing grammatical structures that are each other's translations. The theory of SynCFGs borrows from syntax-directed transduction and syntax-based machine translation , modeling the reordering of clauses that occurs when translating a sentence by correspondences between phrase ...
a word-by-word or morpheme-by-morpheme gloss, where morphemes within a word are separated by hyphens or other punctuation, and finally a free translation, which may be placed in a separate paragraph or on the facing page if the structures of the languages are too different for it to follow the text line by line.
MT may be based on a set of linguistic rules, or on large bodies (corpora) of already existing parallel texts. Rule-based methodologies may consist in a direct word-by-word translation, or operate via a more abstract representation of meaning: a representation either specific to the language pair, or a language-independent interlingua.
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).
Transliteration is the process of representing or intending to represent a word, phrase, or text in a different script or writing system. Transliterations are designed to convey the pronunciation of the original word in a different script, allowing readers or speakers of that script to approximate the sounds and pronunciation of the original word.
Apertium is a transfer-based machine translation system, which uses finite state transducers for all of its lexical transformations, and Constraint Grammar taggers as well as hidden Markov models or Perceptrons for part-of-speech tagging / word category disambiguation. [2]