Evolution of modern machine translators

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HL content: Modeling & Simulation[1]

Machine translation, (sometimes referred to by the abbreviation MT) is a sub-field of computational linguistics that investigates the use of software to translate text or speech from one language to another.

On a basic level, MT performs simple substitution of words in one language for words in another, but that alone usually cannot produce a good translation of a text because recognition of whole phrases and their closest counterparts in the target language is needed. [2]

Evolution of machine translators[edit]

  • Rule-based machine translation
uses dictionaries and a set of linguistic rules to translate between two languages. [3]
  • Example-based Machine Translation
uses ready-made phrases as examples instead of repeated translation. [4]
  • Statistical Machine Translation
the machine tries to recognise patterns by studying similar texts without the need for dictionaries or rules. [5]
  • Neural Machine Translation
uses a large artificial neural network to predict the probability of a sequence of words.[6]

Our ultimate goal[edit]

Instant, perfectly accurate translation. Click here for a funny take on this

Standards[edit]

  • Outline the evolution of modern machine translators.

References[edit]

  1. http://www.flaticon.com/
  2. https://en.wikipedia.org/wiki/Machine_translation
  3. Sheevankit the awesome
  4. Sheevankit the awesome
  5. Sheevankit the awesome
  6. Sheevankit the awesome

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