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The study aims to improve machine translation of long English sentences by focusing on semantic relations to reduce errors.

Research on machine translation of clauses in long English sentences based on semantic relation

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The study aims to improve machine translation of long English sentences by focusing on semantic relations to reduce errors.
Integrated a long-sentence segmentation module using semantic vectors into a GRU-based translation algorithm.
Developed an experimental dataset from the Tsinghua Chinese-English parallel corpus.
Conducted simulation experiments to test segmentation accuracy and translation performance.
The segmentation module achieved an average precision of 0.97, recall rate of 0.96, and F-score of 0.96 across varying sentence lengths.
The optimized translation model achieved a BLEU score between 0.483 and 0.486, significantly higher than traditional algorithms.
Translation outputs showed stronger alignment with manual translations, enhancing accuracy and syntactic adaptability.

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Randomized trial demonstrates improved translation accuracy in long English sentences, suggesting enhanced semantic processing.

Lin Jing (2026) studied this question.

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