Machine Translation (MT)

MT has been explored and tested for many years. Originally the goal was defined very simply: process an input text in one language and produce and output text in another language, such that the meaning remained unchanged.

The following components of language must be considered during translation:

Machine translation is a very complicated process because the source and destination languages may be very alien. Also, slang, idioms and other regional dialects confuse the process even further.

MT Methods

A process of choosing appropriate word meaning, like the one used by Quillian (1967) is extremely important in machine translation, where choosing the incorrect meaning of the word during translation could totally change the meaning of a translated sentence.

General structure of MT programs:

  • Syntactic analyser creates syntactic parse tree

  • Syntactic transformations modify the syntactic parse tree for the destination language
  • A language generator builds the target sentence from the parse tree

Stages of Language Generation:

  1. Dictionary look-up and morphological analysis
  2. Identification of homographs
  3. Identification of compound nouns
  4. Identification of noun and verb phrase
  5. Processing of idioms
  6. Processing of prepositions
  7. Subject-predicate identification
  8. Syntax identification

The field of machine translation has recently come of age. Many packages are available for home PCs are affordable prices. However, the quality of these applications is still rather poor. Part of the problem is that efficient machine translation requires neural networks, and until parallel processors are more affordable, software emulation must be used. This software emulation is slow, and so quality is compromised so that a reasonable speed can be achieved.