In today’s globalised world, the need for translation tools has become more apparent than ever before. With the advent of the internet and the proliferation of online information, the demand for accurate and efficient translation has never been greater.
A variety of translation tools are available to help individuals and businesses alike, but which ones are the most effective? And is the job of a translator at risk of being taken over by digital, intelligent tools?
Translation using computer technology is by neural machine translation or NMT — typically software used to translate words from one language to another.
Such tools use artificial neural networks to learn from large amounts of bilingual text data and can produce more accurate and natural-sounding translations than traditional apps.
DeepL is a leading neural machine translation tool that uses artificial neural networks to learn from large amounts of bilingual text data and produce more accurate and natural-sounding translations.
DeepL has been gaining popularity in recent years and is considered by many to be one of the most effective translation tools available.
Nuances of language
One of the advantages of DeepL is its ability to capture the nuances of language and cultural context accurately. Unlike traditional machine translation tools, which often produce awkward or unintelligible translations, DeepL can produce more fluent translations and natural sounding.
Because it is an online tool, users can quickly and easily upload their text and receive a translation in seconds. This is particularly useful for individuals and businesses that need to translate large amounts of text regularly.
Furthermore, DeepL supports a wide range of languages, including many that are not commonly supported by other translation tools.
This makes it an ideal choice for individuals and businesses who need to translate text into less commonly spoken languages.
Tools like DeepL have limitations. While it can produce more accurate and natural-sounding translations than traditional MT tools, it still needs help to accurately capture the subtleties of language and cultural context in certain situations.
Additionally, it is sometimes unclear how DeepL’s algorithms decide which translation to use in each situation, making it difficult to identify and correct errors.
As machine translation technology continues to improve, more and more basic translation tasks will likely be automated, reducing the demand for human translators in certain areas.
However, it is also possible that the demand for more complex translations that require a deep understanding of language and cultural context will continue to increase, providing new opportunities for human translators.
Also, as businesses and organisations become more specialised, there is likely to be greater demand for translation and interpretation services in niche areas such as legal, medical, and technical fields. These specialised areas require a deep understanding of the subject matter and linguistic and cultural expertise.
Mr. Wambugu is a Certified Cloud and Cyber Security Consultant. Email: [email protected] Twitter: @Samwambugu2