机器翻译中的神经网络

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引用次数: 0

摘要

本文介绍了机器翻译的主要发展阶段,以及可用于翻译工具的神经语言学原理。对神经网络是否具有进行仿真的能力提出了一些假设。展望了GLOM理论将如何改变未来的机器翻译领域。目的是探索机器翻译领域的神经网络,考虑其进一步发展的前景,并推导出允许神经网络模拟神经语言过程的原理。这一目的将通过以下行动来实现:分析机器翻译的各种方法以及人脑中的神经语言学过程。根据收集到的数据,确定了神经网络设计的原则。作者对基于GLOM的神经网络的发展做了一些假设。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
NEURAL NETWORKS IN MACHINE TRANSLATION
The article presents the main development stages of the machine translation and the principles of neurolinguistics that can be used for translating tools. Some assumptions about whether neural networks are capable of performing simulation are provided. It is considered how the GLOM theory can change the field of machine translation in future. The purpose is to explore neural networks in the field of machine translation, consider the prospect of their further development and derive principles that will allow neural networks to simulate neurolinguistic processes.This purpose is going to be achieved through the following actions: the analysis of various approaches to machine translation along withneurolinguistics processes in the human brain. Based on the data collected, principles of neural network design are determined. The authors make assumptions about the development of neural networks based on the GLOM.
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