傅立叶变换理论在机器翻译中的应用

Galyna Kharkevych, Yurii Kharkevych, I. Kal’chuk, V. Sobchuk
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引用次数: 5

摘要

本文致力于基于傅里叶变换理论的机器翻译研究。科技进步导致了科技信息量的增加。译者应付不了这种信息流。由于翻译的高度标准化,使用机器翻译是有效的。统计机器翻译是在统计模型的基础上生成的。统计机器翻译的任务不是翻译文本,而是解码文本。在此工作中,我们提出了基于傅立叶级数求和方法的傅立叶变换技术在统计机器翻译中的应用,该方法由自然参数函数集给出,而不是现有的函数集。该技术提高了机器翻译的效率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Usage of Fourier transformation theory in machine translation
This paper is devoted to the study of machine translation based on Fourier transformation theory. Scientific and technological progress has led to the increase in the volume of scientific and technical information. A translator cannot cope with this flow of information. The use of machine translation is effective because of the high standardization of translation. Statistical machine translation is generated on the basis of statistical models. The task of the statistical machine translation is not to translate the text but to decode it. In this work, we propose to use Fourier transformation technique in statistical machine translation based on the methods of summation of Fourier series given by the set of functions of natural argument as opposed to existing ones. The proposed technique increases the efficiency of the machine translation.
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