Machine translation (MT) is a subfield of artificial intelligence that uses software to translate text or speech from one language to another. It is an automated process, intended to replace or support human translators in translating vast amounts of text in a quick and efficient manner.
It's widely used in services such as Google Translate, Microsoft Translator, and many other online platforms.
How Machine Translation works
Machine translation operates based on two primary methods: rule-based (RBMT) and statistical (SMT), with the more recent development being neural machine translation (NMT).
Rule-based machine translation relies on countless linguistic rules and millions of bilingual sentence pairs to translate from one language to another. The rules are crafted by linguists and involve grammar, syntax, and semantic patterns.
Statistical machine translation, on the other hand, does not depend on linguistic rules. Instead, it generates translations based on statistical models. This means it translates texts based on the analysis of bilingual text corpora (a large and structured set of texts).
Neural machine translation is the most advanced technique. It uses a large artificial neural network to predict the likelihood of a sequence of words, typically modeling entire sentences in a single integrated model.
The translation process typically consists of multiple components: first, the source text is analyzed and transformed into an intermediary, language-neutral format. Then, the target text is generated from this format. These processes are aided by the use of translation memory, which stores previously translated sentences, paragraphs, or phrases in a database to aid in future translations.
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