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→How does machine translation work?
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=Research questions= | =Research questions= | ||
===How does machine translation work?=== | ===How does machine translation work?=== | ||
There are two general approaches to Machine Translation. Most of the early work, before massive corpora, was done with Rule-based machine translation ( [http://en.wikipedia.org/wiki/Rule-based_machine_translation] ). However, most of the current work being done is with Statistical Machine Translation ( [http://en.wikipedia.org/wiki/Statistical_machine_translation] ). A brief description of each is available below. | |||
====Rule-Based Machine Translation==== | |||
Uses pre-defined grammatical and syntactic rules and large bilingual dictionaries to translate text. It can be very costly to produce the necessary resources for this type of translation but according to [http://blog.globalizationpartners.com/machine-translation.aspx] it can actually "produce better quality for language pairs with very different word orders (for, example English to Japanese)" | |||
====Statistical Machine Translation==== | |||
Uses statistical information to choose the "best" translation from the possible translations of a text. As far as I know, all work with statistical machine translation requires a bilingual corpus for calculating the necessary probabilities. | |||
===What are the benefits and drawbacks to each methodology?=== | ===What are the benefits and drawbacks to each methodology?=== | ||