首页|Reports from Jiangxi University of Technology Advance Knowledge in Machine Translation (Optimization of Translation Techniques be- tween English and Chinese Literary Works in the Information Age)
Reports from Jiangxi University of Technology Advance Knowledge in Machine Translation (Optimization of Translation Techniques be- tween English and Chinese Literary Works in the Information Age)
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2024 FEB 02 (NewsRx) – By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Researchers detail new data in machine translation. According to news reporting originating from Jiangxi University of Technology by NewsRx correspondents, research stated, “Under the background of cultural globalization, English-Chinese literary translation plays an important role in which it is not only a process of language conversion, but also a process of cultural conversion.” The news editors obtained a quote from the research from Jiangxi University of Technology: “In this paper, the BiGUR-LM-Attention optimization model is fused and constructed using the WordNet semantic similarity model, GRU-LM one-way gated similarity model, and BiGR-LM two-way gated similarity model. The LDA theme model is selected to generate the 3-layer Bayesian network structure of literary works’ paragraphs, themes and words to obtain the probability information that represents the highest attention of the work’s text theme, which constitutes the attention mechanism feature word vector. Finally, five classic literary works are selected as the training corpus to compare and analyze the translation quality between machine translation and human translation in the mutual translation of English and Chinese literary works.”
Jiangxi University of TechnologyEmerging TechnologiesMa- chine LearningMachine Translation
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