基于深度学习的农机机器英语语料库的设计  

Design of an English Corpus for Agricultural Machines Based on Deep Learning

作　　者：徐威 Xu Wei(Wuhan Qingchuan University,Wuhan 430204,China)

机构地区：[1]武汉晴川学院,武汉430204

出　　处：《农机化研究》2024年第10期208-212,共5页Journal of Agricultural Mechanization Research

基　　金：湖北省教育厅人文社会科学研究项目(18G070)。

摘　　要：随着农业机械的智能发展,语言逐渐成为人机交互的重要方式,故建立有效的机器语言翻译模型对于提高智能农业装备的使用性能具有重要的推动作用。随着深度学习及神经网络技术的快速发展,目前已经形成了多元化机器语言翻译模型,并取得了良好的应用效果。为此,以智慧农业和自然语言处理为研究基础,构建了智能农业机械英汉双语语料库。研究结果表明:提出的模型具有良好的应用效果,且在准确率和机器翻译的效率方面都明显优于传统翻译方法,可为智慧农业的发展提供可靠的双语模型。With the intelligent development of agricultural machinery,language gradually becomes an important way of human-machine interaction,therefore,establishing an effective machine language translation model has an important role in promoting the use performance of intelligent agricultural equipment.With the rapid development of deep learning and neural network technology,diversified machine language translation models have been formed and have achieved good application results.This study takes intelligent agriculture and natural language processing as the research basis and constructs a bilingual corpus of intelligent agricultural machinery in English and Chinese as the research goal.The results show that the model proposed in this study has good application effects and is significantly better than other translation methods in terms of accuracy and efficiency of machine translation,and provide a reliable bilingual model for the development of smart agriculture.

关 键 词：智慧农机 深度学习 机器翻译 

分 类 号：S126[农业科学—农业基础科学]