Hence the development of neural machine translation, which uses deep learning techniques and artificial intelligence to determine the best translation for a certain text. While statistical machine translation did a fair job of text translation, there is always room for improvement. From there, the statistical machine translation system applies prediction algorithms to churn out translations best adapted to the source text. After that, it crawls through massive amounts of human-translated text – known as bilingual text corpora – to find all examples of “bits” in these texts and their translated equivalents. This technology breaks the source text up into “bits” (such as words, phrases, and syntactical arrangements). Next came statistical machine translation, which did somewhat better at translating text. However, such rules-based, word-for-word machine translation wasn’t the most accurate and often required substantial “post-editing,” or manual revision by human translators, afterward. The machine translator would pull up the relevant language pair dictionary, then use grammatical rules and direct, literal translation to translate text. The very first version of machine translation was quite primitive and involved translating text according to set rules. To understand how DeepL and Google Translate came into being, we first need to understand the origins of their technology – namely, neural machine translation. How Did Deepl and Google Translate Come Into Being? We’ll also do a comparison of DeepL vs Google Translate to evaluate their pros and cons, before sharing our recommendation of the best website machine translation solution. So to help you secure the best machine translations for your website, we’re going to explore the backgrounds of Google Translate and DeepL (and their underlying technologies). But if you aren’t a professional translator, DeepL may be a more unfamiliar name. You’ve probably heard of and used Google Translate at least once in your life. While there are many machine translation systems available, two of the most reputable ones are Google Translate and DeepL. It’s therefore unsurprising that the volume of machine-translated-web content has increased six times over the last two years! Machine translation technology can translate text – especially large quantities of it – much faster than any human can, and at a much lower cost. If you’re looking to translate your website to serve customers in different languages, there’s no better technology available today than machine translation.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |