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How are researchers using semantics to improve machine translation?

Jamie M'Quharg

Researchers are using semantics to make machine translation smarter and more like humans. Semantics is the branch of linguistics that studies meaning in language. They use it to help computers understand what the words mean so they can translate sentences more accurately.

Before, computers would just translate words literally, one by one. But we know that sometimes words have different meanings based on the context they're in. For example, the word "bank" can mean a place where you keep your money or the side of a river. Using semantics, computers can understand which meaning is correct in each case.

Researchers are also using machine learning to train computers to understand more and more language patterns. They give the computer many examples of sentences and their translations, and the computer learns to recognize the patterns and create its own translations.

Another way semantics helps with machine translation is by looking at the structure of a sentence. Languages don't always follow the same order of words in a sentence, and sometimes the meaning can change if the order is different. Semantics helps the computer understand the structure of both the original sentence and the translated sentence.

Thanks to all this research, machine translation is becoming more and more accurate. It's not perfect yet, but it's getting better all the time!