Sun’iy intellekt yordamida ispan tilidagi sinxron tarjima jarayonini optimallashtirish

Abstract

Artificial intelligence (AI) technologies enable significant optimization of both word-for-word and context-based translation processes. This study analyzes the effectiveness of AI models, particularly deep learning and natural language processing (NLP) algorithms, in synchronous translation systems operating in the Spanish language. The article examines AI strategies aimed at improving translation accuracy, contextual adaptability, and processing speed, as well as investigating the technical and linguistic constraints inherent in real-time translation processes.