The concept of machine translation has been around for a while. First established as a branch of computational linguistics, the idea of this type of translation has been around since the 17th century. But the field of machine translation began to gather steam in the early 50s when Georgetown University and IBM teamed to create a public demonstration of the concept.
A simple explanation is that this type of translation is merely an algorithm, like any other computer program. But unlike other computer programs, this algorithm has to adapt itself to the ever-evolving subject of language. It has to learn to perform its functions accurately while adapting to changes in the world’s languages.
Languages continue to evolve as the world changes. It’s why dictionaries need to be revised continually. As words are revised, and the meanings of some words can change depending on the context of the sentence, it presents challenges for even the most skillful translator.
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This type of technology is always learning by constant repetition and continuous input. The learning algorithm is complicated in its functions, but understandable even to the layman because of an accurate model that was introduced back in 1968.
The model visualized a triangle with the wide end on the bottom and the pointy end on top. Each translation has a source sentence in the original language that is represented by the left side of the triangle. It also has a target sentence that is in the intended language. This is represented by the right side of the triangle.
The narrower top end of the triangle represents the basic translation functions. Matching nouns to nouns, verbs to verbs and articles to articles. As the triangle widens, it represents the more complicated functions that are handled after the simple functions – matching adverbs to verbs, pronouns to nouns and so on.
This algorithm can have many levels of translation, depending on the complexity of the language, whether its alphabet or character-based and the complexity of matching one language with another. For instance, translating from English to German is relatively simple because of the commonality of the two languages. But translating Chinese into Arabic can take many complex steps because the two languages have nothing in common.
How Machine Learning Can Help Online Businesses
Most people who have used the internet a lot, have experienced using Google Translate. This is the world’s most widely used machine translation program.
But Google Translate provides a general, written translation. Companies can invest in translation programs that are programmed to learn spoken words and translate them instantly into another language. This ability makes centrally-located customer service centers possible.
By employing this type of technology, a Japanese customer service representative can answer questions from a Portuguese-speaking customer in real-time.
Machine translation is something that every company seeking to conduct business online as their primary business model should investigate. It will be the communication tool of the future that enables true globalization.