Evolution of AI in Interpretation: From Traditional Approaches to Real-Time Solution

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Author(s): Andi Asrifan (Universitas Negeri Makassar, Indonesia)and Mohammed H. Alaqad (University of Malaya, Malaysia)
Copyright: 2025
Pages: 32
Source title: Role of AI in Translation and Interpretation
Source Author(s)/Editor(s): Mohammed H. Al Aqad (University of Malaya, Malaysia)
DOI: 10.4018/979-8-3373-0060-3.ch003

Keywords: Artificial Intelligence / Computational Linguistics / Computer Science & IT / Engineering Science Reference

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Abstract

Traditional methodologies have become real-time solutions thanks to AI in interpretation, improving cross-language communication. Traditional approaches like consecutive and simultaneous interpretation relied on human skill, which was effective but slow and inaccurate. Neural machine translation (NMT) and deep learning have made context-aware, scalable, and efficient language processing possible. AI interpreters now capture complex language, idioms, and cultural subtleties, enhancing translation quality. Managing cultural sensitivity and algorithmic bias requires a hybrid approach that blends AI and human control. This integration preserves human communication while using AI's speed and efficiency. As AI evolves, its interpretation role will be crucial to global communication and understanding.

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Evolution of AI in Interpretation: From Traditional Approaches to Real-Time Solution

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