Amiri, Sayed Mahbub Hasan (2025) The babel fish of the digital age: Natural language computing as a universal translator. International Journal of Science and Research Archive, 15 (3). pp. 927-939. ISSN 2582-8185
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Abstract
Natural Language Computing (NLC) the intersection of natural language processing and artificial intelligence is poised to overcome these barriers with neural machine translation, real-time multilingual translation platforms and emotion-aware systems. This article follows the evolution of NLC from its early rule-based approach to the transformer-driven models we see today and discusses its transformative applications across healthcare, humanitarian aid, business and entertainment. But the road to a universal translator is littered with obstacles: AIs have trouble with cultural nuance, tend to amplify biases that favor dominant languages, and risk wiping out linguistic diversity. Emergent technologies like context-aware architectures, decentralized AI, and augmented reality integration show us the core of the future bridging divides without homogenizing expression. But ethical considerations hang over these developments can machine truly mirror the empathy of human translators, and how do we reconcile progress and cultural protection? This article makes the case, through advocacy for inclusive design, community driven models and strong ethical guardrails, that NLC’s real power is not about replacement of human language, but rather enhancement of its fullness. Only through a content creation and translation process that is equitable, sustainable, and respectful of global diversity can we hope to achieve a truly language agnostic world.
Item Type: | Article |
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Official URL: | https://doi.org/10.30574/ijsra.2025.15.3.1839 |
Uncontrolled Keywords: | Natural Language Computing; Universal Translator; Ai Ethics; Neural Machine Translation; Linguistic Diversity; Multilingual Ai; Augmented Reality |
Depositing User: | Editor IJSRA |
Date Deposited: | 27 Jul 2025 15:06 |
Related URLs: | |
URI: | https://eprint.scholarsrepository.com/id/eprint/2342 |