10 Little Translation Mistakes That Caused Big Problems
Learning a foreign language is achievable, but it comes with numerous challenges. Despite conversational ability, grammar rules may occasionally be forgotten, resulting in translation errors.
Some non-standard cases of language use cause the main difficulties when it comes to translating social media posts. Puns and jokes made by wordplay are extremely challenging for artificial intelligence to process and recognize, so their translation in most cases loses both the original meaning and often even any sense. Slang and some newly coined words are also obstacles in machine translation. On Instagram, as well as other social media networks, it is very topical as posts and captions very often use some ‘trendy’ or clipped words and contractions. On accounts of some funny animals, one can often see words like ‘hoomans’, ‘frens’ etc. that are easily recognizable both by native speakers and ELLs but not by artificial intelligence, which complicates their correct translation.
Apart from some qualities inherent in language that make machine translation in social media contexts very hard, the technology used by Instagram in itself is far from being perfect. From a simple check on a feature of translation in a few posts’ captions, it is clear that machine translation used by Instagram works simply by translating each individual word with only some sporadic attempts of the subject-verb agreement without any deep analysis of structures. Captions always are translated in a second or less, which also suggests only some superficial work of the machine translation engine. Unlike in Google Translator, one cannot suggest their own translation to a specific word that also does not allow the technology to develop further.
Read also: Who can do SDS translation properly?
Collaboration with our translation company that offers human translation can help Instagram machine translation to understand the lexicon of the users and especially the non-standard speech often observed in captions. We can research and process thousands of text samples available on Instagram to help the AI process it in a meaningful way. Human translation of captions can be a rich source for a machine translation to understand natural language better. It can serve as a basis for machine learning and the further growth of the technology’s potential to make translation more fluent. Creating a database of some frequently used slang words can help Instagram to make their translation more accurate and extend their vocabulary. With samples of correct translation and the lists, the popular non-standard words the specialists that develop machine translation technology used by Instagram can improve the quality of their product.
TheWordPoint is a company that provides quality human translation to and from almost 100 languages and constantly extends this number. We have a global team of professional certified translators and who work on translation, localization, and editing for clients all over the world. Our client’s needs are of utmost importance for us, and we deliver reliable, unique services in a variety of fields such as business, IT, education, science, personal correspondence, and many more. TheWordPoint is a company that strives for excellence and quality work to help connect individuals and enterprises around the globe.
Learning a foreign language is achievable, but it comes with numerous challenges. Despite conversational ability, grammar rules may occasionally be forgotten, resulting in translation errors.
In today’s global economy, the concept of “free movement” is almost essential for the existence of singular yet interconnected market spaces; an economic system in which services, goods, labour, and capital circulate without hurdles but within pre-stipulated regulations.
The concept of machine translation systems has been known and developed for the past 50 years. In the beginning, such systems were used solely and carefully by research entities, large companies and governmental bodies that also helped to finance them.
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