Machine-Learning Translation Can Never Replace Human Translators?

Nelson Mandela rightly said, “If you talk to a man in the language he understands that goes to his head, but if you talk to a man in his language that goes to his heart.”

Perhaps you have never spoken the language ofthe country you are residing in, or you know the language, but find that you cannot communicate with the locals; perhaps you can communicate, but seldom have difficulty getting some of the jargon and popular expression that you hear as you speak with the natives. Whatever the problem, there is almost always a language barrier when you are in overseas, unless you are a fluent speaker. In that condition, language translation helps you to fill the language and cultural gap between the innate & the outsider.

In India, where there are hundreds of languages, it’s obvious that you will have employees, client or be it a common man who doesn’t speak your language and so, it is hard to give direction, explain your expectations, or provide performance feedback to those with whom you cannot communicate effectively. This is why; there is always a battle for the win between language translation agencies in Delhi and the machine-learning applications worldwide while both have seen a great upshot in past ten years.

Human Translator vs. Machine Translation

A human language translator is a learned man who has picked up dominance over both the source and target dialect. Tools like Amazon Translate and Google Translate makes the job easy for both the translator as well as the foreign man.  For machine-learning devices, interpretation alludes more to decipher the source language from word to word and less to do with the culture of the source dialect in this way, it extends the voids. But a human interpreter offers the social pith of a community, local, state or nation which keeps up the aestheticism and realness of source language.

Professionals don't depend on machine interpretation since tech-algorithm many times does not accurately recognize the local dialect terms and their suggestions. Hence, it is a challenge for the AI to compete with human cognitive insights.

On-growing Demand of Translators and Applications

The expanding worldwide exchange has resulted in the boom of translation services. While the standard translation or real-time translation is easily overseen through Google Translate, multi-national companies are opting for human translators for engaging with the global audience. Since machine-learning & AI, instruments are restricted to literal translation, human interpreters & translators play a major role in pragmatic, ethnographic, aesthetic-poetic, etymological interpretation, communicative and semantic interpretation.

Web engineers are continually formulating new plans, strategies, and everything to create Interlingua of all human dialects. But the innovation, doubtlessly, cannot supplant the cognitive capacity of a human.