Machine translation (MT) is a sub category of computational linguistics. Computational linguistics investigates the software use to translate as well as speech between different languages.
For any translation process, automated or human, the meaning of content in the source language must be completely restored in the translated language. On the front it seems too easy, but, it is much complex in reality. Translation is not simply word to word substitution. It is important for a translator to interpret and analyse all the elements of the text and consider how different words influence each other. The translator must be expert in syntax (structure), grammar, semantics (meanings), in the source as well as target languages. They must be familiar with local regions also.
Machine and human translation have their own set of challenges. As an example, no two different translators can produce same translated content of the same source content. It may require a number of revisions to meet customer needs. The greatest challenge is that how machine translation produces quality translations.
Machine translation system has two main types: statistical and rule based.
The Statistical translation system does not have any knowledge of grammar and language rules. They translate by interpreting the big heap of data for every language pair. These translators can be educated with specific disciplines and industries by using data that is relevant to the needed sector. Normally statistical system provides more fluent result and less consistent translations.
The rule based system uses a combined form of grammar and language rules plus dictionaries. Special dictionaries have been created to focus on different disciplines and industries. This type of translation typically gives a consistent translation and accurate terminology while skilled with special dictionaries.
This Simultaneous Translator is a very good tool for translators. The tool helps them for any unknown word. It also helps to choose the way of the sentence so that it may provide the same results of popular machine translators; Google, Bing and Yandex.
The above mentioned tool provides the facility of machine translation detector, that helps to find if the text is translated from any tool or not. The tool also allows for customization like weather reports. The technique is effective in those areas where formulaic or formal language is used. Machine translation of legal and government documents produces useful output than less standardize text. Better quality can also be achieved by the intervention.
The benefits of Machine translation are as follows:
Deliver translation faster, increased productivity:
Flexibility and choice, saves time, suits all project types:
It is concluded that the tool is best to use because of its numerous features. Giving the structure of the text and three different translators makes the tool different and reliable.