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With the rapid development of globalization, communication between different countries has become increasingly frequent. In order to solve the problem of low accuracy of traditional English translation Machine translation, this paper used GloVe-CNN (Global Vectors for Word Representation-Convolutional Neural Networks) algorithm to build an English translation machine intelligence model, which would intelligently translate the main idea and context of the whole article when translating, and could effectively solve the problem of ambiguity in some structures. It could be trained and learned through continuous use of English literature, updating and enriching its corpus, and improving the accuracy of its translation. The experiment proved that the accuracy of the English translation machine intelligent model established using the GloVe-CNN algorithm in this article was between 96 and 99, which was more than 25% higher than traditional English translation machine models. The intelligent translation model could intelligently recognize and translate based on the main idea and contextual connections of the article.

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English Machine Translation Intelligent Model Recognition Based on GloVe-CNN Algorithm

  • 会议论文

  • 发表日期：

    2025年

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  • Bo Huang,
  • Yunxia Zhang

摘要

With the rapid development of globalization, communication between different countries has become increasingly frequent. In order to solve the problem of low accuracy of traditional English translation Machine translation, this paper used GloVe-CNN (Global Vectors for Word Representation-Convolutional Neural Networks) algorithm to build an English translation machine intelligence model, which would intelligently translate the main idea and context of the whole article when translating, and could effectively solve the problem of ambiguity in some structures. It could be trained and learned through continuous use of English literature, updating and enriching its corpus, and improving the accuracy of its translation. The experiment proved that the accuracy of the English translation machine intelligent model established using the GloVe-CNN algorithm in this article was between 96 and 99, which was more than 25% higher than traditional English translation machine models. The intelligent translation model could intelligently recognize and translate based on the main idea and contextual connections of the article.