Will Machine-Learning Translation 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.”

If you ever been to a foreign land (foreign in both culture & language), you would have experienced the communication gap between the natives and you. You don’t know what they speak in Arabic, and they don’t know what you speak in Hindi. While English became a universal language overseas a long time back facilitating the filling of communication gap, there is always a cultural void left behind all the time. In such a case, language translation fills this language and cultural gap between the native & the outsider.

In India, natives speak more than a hundred languages and the oral communication between each other is made possible through a bridging language (parole). But because a common or bridging language can be effective in information conveyance, it can not necessarily bring the pure cultural essence of one’s own language, as Mandela said. Information or fragmented sentences can be understood but not felt or truly connected. This is why; there is always a battle for 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

The human translator is a learned man who has gained mastery over both the source and target language. However, Amazon Translate, and Google Translate are some of the machine-learning software that make the job of human translator as well as of a foreign man to find an easy way back to home. For machine-learning tools, translation refers more to translate the source language from word to word and less to do with the context and culture of the source language thus, deepening the voids. But a human translator shares the cultural essence of a community, region, state or country which maintains the aestheticism and authenticity of source language.

Professionals do not rely on machine translation because tech-algorithm many times does not correctly identify the native language terms and their implications. Therefore, it is a challenge for the AI to compete with human cognitive intelligence.

On-growing Demand of Translators and Applications                         

Due to the increasing opportunities of international trade, language translation services are on boom. While the standard translation or real-time translation is easily managed through Google Translate, multi-national companies are opting for human translators for engaging with global audience. Because machine-learning & AI tools are good at literal translation only, human translators & interpreters play major role in pragmatic, ethnographic, aesthetic-poetic, linguistic translation, communicative and semantic translation.

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Created on May 26th 2018 02:31. Viewed 478 times.

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