Machine Translation Response - Afiq

 I've always been fascinated about machine translation and natural language processing. How is something that cannot actually think the way humans do and feel the way humans feel able to accurately translate sentences with the right nuances across different languages? And the answer up until this point is that they can't, not to the extent a human native in said language would be able to express themselves.

Both the articles "Translation of the Future" and "Finding a Voice" bring up the same problem in which MT faces up until now, and that is to translate based on earlier context. In the former article, it is mentioned that a way to combat improper translations of terms in certain professional fields is by creating a model that trains itself only from professional domains. I believe that translating professional texts is more efficient and doable in this manner as texts of that nature usually impose strict and standard rules of writing in order not to cause any vagueness or misinterpretation of the article in its original language. 

I believe that a lot of the problems arise when MTs are expected to flawlessly translate everyday conversations and creative writing, as standard writing rules are not always followed or sometimes manipulated by the author/speaker. This is why the early rules-based approach mentioned in the "Finding a Voice" article was not entirely successful in translating sentences. The phrase-based approach taken after is a lot more successful as it takes the probability of the word appearing in consideration with the words surrounding it, which does play with the "looking into context" part of a human's speech processing.

I do believe, however, that MT can never be fully independent in translating sentences perfect for its situation. At best, MT can do most of the work for humans, but the final touch-ups in making it coherent and flow best with the surrounding sentences and context must be done by humans, and even then, a lot of people don't get it right. I believe this to be because if even humans themselves can't get whatever they say right in certain contexts, how is MT, built by and learns from the very same humans, ever get it perfect? It is however, an amazing tool for people who wants to simple be able to understand and translate the gist of a certain sentence. 

Japanese Sentence:

私、ちょっと好きだな、この人。バターをざりざりと伸ばしつつ、お天気お姉さんを眺める。雪国めいた肌の白さが、なんとなく北国の出身かなと思わせる。

DeepL Translation:

I kind of like this guy. I looked at the weather girl as I slathered butter on her skin. The whiteness of her skin, which is reminiscent of snow country, makes one wonder if she is from a northern country.

My Translation:

I kinda like her, this weather girl. I pay attention to what she says while spreading the butter. The snow-like tone of her skin makes me think she’s from the North.