Human Vs. AI Translation: Which One Is Better?

Script:

• What does the process of language acquisition look like?
  • Humans undergo a series of complex steps to learn a language.
  • The perception of speech, language, and other noises begins as early as in the womb.
  • Newborns quickly learn to distinguish language from other noises they hear.
  • After just six months, babies begin to develop an understanding of their native language.
  • Between the ages of one and two, word acquisition improves and through experience they can start to interpret sentences.
  • By the age of 5, the average child possesses a passive vocabulary of around 14,000 words.
  • But, what is the neuroscience behind learning additional languages beyond your native language? How can human translators shift between multiple languages with ease?
• The Neurological Process of Human Translation
  • Shifting from one language to another during the translation process involves several regions of the brain.
  • When a person translates a text or interprets another person’s speech, the temporal lobe of the brain helps them decipher meaning.
  • The frontal-temporal network, the motor cortices, the basal ganglia, and the cerebellum are activated as well.
• How does AI translation work?
  • Today’s AI translation software are based on neural machine translation (NMT).
  • NMT uses deep learning to learn new languages and then continuously improves on that knowledge as it receives new input.
  • Unlike other machine translation methods, NMT software work with massive data sets and identify linguistic patterns and relationships in order to learn languages.
  • The most recent breakthrough in neural machine translation has been the creation of transformer neural networks.
  • Using “self-attention”, transformers selectively focus on different parts of an input sentence, weight their importance based on how relevant they are to each other, and identify important relationships in order to translate text.
• Conclusion
  • For humans, language learning is a complex, multi-year process.
  • When translating, several brain regions get activated and help us decipher meaning.
  • On the other hand, AI relies on the data provided by its human creators in order to translate content. The lack of human input can cause AI-generated translations to be inaccurate.
  • For example, while many government and aid organizations prefer to use AI-generated translations when processing immigration documents, inaccurate translations have caused potential immigrants to lose their asylum bids.
  • Clearly, at present, only humans understand the nuances of language and can creatively solve complex linguistic needs.

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