"Limitations and Challenges of Deep L Machine Translation"

DeepL has some limitations despite being recognized as one of the good translation tools.Limited Languages:  Although DeepL supports multiple languages, the number of supported languages is still less compared to some others AI. At present, DeepL can translate 11 languages - the majority being European languages.Limited Features: Compared to some other translation tools, DeepL may lack additional features such as translation of more complex documents or wider integration with other applications. Beside that, they have less options for voice translation.
Lack of emotional nbuances:
DeepL also often struggles to capture the emotional nuances contained in the text. Automatic translation may not be able to reproduce the feeling or tone that the author is trying to convey, making the translation feel flat and lacking depth.
Errors in Idioms and Expressions: Idioms and expressions are often a challenge for translation engines like DeepL. Direct translation of these expressions can result in inappropriate or even absurd meanings, as idioms often have cultural meanings that cannot be translated literally. Inability to handle these expressions can lead to significant misunderstandings.
Lack of Human Touch: Finally, one of the biggest drawbacks of DeepL is the lack of human touch in the translation process. Machines cannot replace the understanding, intuition and interpretation that human translators possess, especially when dealing with complex cultural contexts. Without this understanding, translations can feel inauthentic and lack the nuance of the origin.

Annisa Tul Khair 21019029

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