Machine translation has continued toadvance exponentially in line with the progress of AI, but its limitationsstill persist. What are some of these limitations? First of all, it can be saidthat interpreting omitted information is difficult. Unconsciously, we oftendon't articulate every component of a sentence perfectly when speaking.Sometimes we miss the subject, other times the object, and quite frequently, wefail to properly handle the end of a sentence. Shall we illustrate this with anexample of a conversation?
These are the lines from the drama<Marry My Husband>. As you can see, there are sentences that do not endperfectly. Also, you can notice instances where the mentioned content isomitted. If we were to write these sentences as complete sentences, the contentwould look like this.
The refined version is grammaticallycorrect, but it might feel awkward when its shown as it is on video. That'sbecause the nature of "speech" is such that when we create sentenceswith all the perfect components, it can actually feel more awkward. We don'tspeak like that in real life. Let's elaborate a bit on the differences betweendocument translation and video translation that arise from these points.
In document translation, sentences oftenhave all their components perfectly structured. Therefore, there isn't as muchconcern about the limitations of machine translation as there used to be.Through ongoing research and development, machine translation systems canproduce fairly accurate interpretations for sentences with perfect structuralelements. However, the issue arises when translating videos, as the limitationsbecome apparent. In cases where sentence components are omitted, as in theexample provided earlier, there are instances where these omissions aren'ttranslated. In cases where the mentioned content is often omitted later,machine translation may fail to accurately translate this part.
Subtitles character count settings areadjustable. Before uploading a project to LETR WORKS, you can set the charactercount in advance, allowing you to establish maximum character limits for easierediting during the subsequent process. This feature helps streamline theediting process, saving both time and effort.
The TB glossary function enables fastertranslation. By unifying repetitive terms in videos, subtitle quality isimproved, leading to more accurate translations.
Utilize Translation Memory (TM) andsentence recommendation features. As you may know, AI improves with learning,yielding better results over time. By learning from past translation projectsat, LETR WORKS, the system can recommend sentences tailored to specificsituations, enabling faster translation.
With increasing interest in the localization ofcontent these days, various fields such as webtoons and videos are attractingattention to translation. This suggests that the importance of colloquialtranslation is expected to grow. At LETR WORKS, we are constantly pondering andproviding solutions for the inevitable limitations of machine translation, soplease continue to show interest and keep an eye on us in the future.
Editor / Lee inhye
inhye.lee@twigfarm.net
