Machine Translation (MT) refers to a machine-based translation of content which is conducted through a fully automated software. Machine Translations provide a good point of reference for translators while translating text and considerably reduces their burden.
- Generic MT can be used to bring out the general meaning of a piece of content, however, it is prone to grammatical, syntax and rhetorical errors as it translates into literal words of the target language. It might not be the best translation, considering it doesn’t take into account the mood, tone or basic emotion being conveyed from the original piece of content. For example- Google Translate, Bing, Naver, etc.
- Customizable MT gives the highest quality of machine translation as it can be trained to improve the accuracy of terminology in any given field (e.g. legal, medical, IP, etc.)
- Adaptive MT is a newer technology that lets you correct the mistakes after an MT output is generated, which will further decrease the likelihood of the same error in the future.
- Rule-based MT (RbMT) uses the grammatical structure, syntactical properties and semantic distinctions in order to translate a piece of content. It is the conversion of the source into literal words of the target language.
- Statistical systems (SMT) refer to providing the best possible translation of a word, in accordance with the surrounding words in a sentence. It takes into account the context of a given text before translating, for better conversions into the target language.
- Neural MT (NMT) can be said to have the most human-like translations. It is because these networks are trained to achieve higher accuracy. Before translating, neural networks try to perceive the full context of the sentence so that when translated, it could become a high-quality translation.
WHEN SHOULD MT BE USED?
If any individual or organization is looking to send across the basic/ general idea of a text, MT is quite convenient and a wise option to explore. However, no MT as of now can beat a professional human translation, as it looks into deeper messages and contexts which isn’t the functionality of a machine. Therefore, to use an MT for conveying some kind of deep-rooted message or context, won’t produce satisfactory results.
Machine Translation can prove to be a very effective means of translation, as it can translate content into any language within a very short time. MT is designed to help ease the process of translation and is very flexible and adaptable to the needs of an individual or an organization in any sector. However, it is not at all advisable to use machine translations for professional work as even a slight error in translation can seriously hamper the firm’s reputations.
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