Machine translation (or MT for short) leverages computer programs to translate text from one language to another. The technology has been around since the 1950s, but has become more commercially viable with the rise of machine learning and artificial intelligence.
There are 3 types of machine translation:
Rules-based machine translation (RBMT) came first and relies on bilingual dictionaries and linguistic rules written by humans. It usually translates one word at a time which can result in awkward sentence structures and other inaccuracies. While RBMT can be useful in some instances, it has many disadvantages including the need for extensive human involvement. This type of machine translation has largely been eclipsed by the other two models.
Statistical machine translation (SMT) translates one language afghanistan mobile database into another by first learning from pre-approved example texts. It then applies a statistical model of the associations between words, phrases, and sentences in one language to the second language. SMT outperforms rule-based machine translation, but can still result in unnatural sounding texts and mistranslations.
Neural machine translation (NMT) uses a kind of artificial intelligence called neural networks to translate from one language to another. NMT is able to learn languages and continuously enhance its performance. Once trained, it is faster and more accurate than SMT. Neural MT is quickly becoming the industry standard in the development of machine translation engines.
What are The Benefits Of Using Machine Translation Software?
The best machine translation software can help you quickly and easily translate large volumes of content such as websites, legal contracts, or product documentation. The main advantages of machine translation are: