一种用于英语长句子快速机器翻译的智能算法

IF 2.1 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Journal of Intelligent Systems Pub Date : 2023-01-01 DOI:10.1515/jisys-2022-0257
Hengheng He
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引用次数: 0

摘要

摘要英语长句的翻译是机器翻译中的一个复杂问题。本文简要介绍了智能机器翻译算法的基本框架,并通过引入长句切分模块和重排模块对基于LSTM的智能机器翻译算法进行了改进。使用公共语料库和包含自收集语言数据的局部语料库进行仿真实验。将改进算法与基于递归神经网络和LSTM的机器翻译算法进行了比较。结果表明,加入长句切分模块和重排模块的基于lstm的机器翻译算法能有效切分长句,翻译英语长句的准确性更高,翻译的语法正确性更强。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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An intelligent algorithm for fast machine translation of long English sentences
Abstract Translation of long sentences in English is a complex problem in machine translation. This work briefly introduced the basic framework of intelligent machine translation algorithm and improved the long short-term memory (LSTM)-based intelligent machine translation algorithm by introducing the long sentence segmentation module and reordering module. Simulation experiments were conducted using the public corpus and the local corpus containing self-collected linguistic data. The improved algorithm was compared with machine translation algorithms based on a recurrent neural network and LSTM. The results suggested that the LSTM-based machine translation algorithm added with the long sentence segmentation module and reordering module effectively segmented long sentences and translated long English sentences more accurately, and the translation was more grammatically correct.
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来源期刊
Journal of Intelligent Systems
Journal of Intelligent Systems COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-
CiteScore
5.90
自引率
3.30%
发文量
77
审稿时长
51 weeks
期刊介绍: The Journal of Intelligent Systems aims to provide research and review papers, as well as Brief Communications at an interdisciplinary level, with the field of intelligent systems providing the focal point. This field includes areas like artificial intelligence, models and computational theories of human cognition, perception and motivation; brain models, artificial neural nets and neural computing. It covers contributions from the social, human and computer sciences to the analysis and application of information technology.
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