机器翻译近十年发展综述——基于CiteSpace可视化分析

Overview of the Development of Machine Translation in the Past Ten Years—Based on CiteSpace Visual Analysis

机器翻译是利用计算机将源语言转换为目标语言的过程,是计算语言学的一个分支,是人工智能在翻译领域的一大进步,具有重要的科学研究价值。随着科技的迅猛发展,机器翻译从“机械大脑”到基于规则的机器翻译和基于统计的机器翻译,再到基于深度学习的神经网络机器翻译,技术上不断推陈出新,算法上不断升级优化。同时,在经济全球化的大背景下,机器翻译技术在促进政治、经济、文化交流等方面起到越来越重要的作用。本文将借助CiteSpace可视化分析来探讨2012年至2022年机器翻译的发展,发现围绕机器翻译主题所引出的研究热点有译后编辑、人工智能等方面,并且机器翻译逐渐与其他学科相结合,形成跨学科研究模式。因此,在未来的发展中,我们要多领域地培养人才,以此促进机器翻译技术创新。

Machine translation is the process of converting the source language into the target language by using computers. It is a branch of computational linguistics and a great progress of artificial intelligence in the field of translation. It has important scientific research value. With the rapid development of science and technology, machine translation has evolved from “mechanical brain” to rule-based machine translation and statistic-based machine translation, and then to neural network machine translation based on deep learning. In terms of technology, it continues to bring forth new ideas, and in terms of algorithms, it continues to upgrade and optimize. At the same time, in the background of economic globalization, machine translation technology plays an increasingly important role in promoting political, economic and cultural exchanges. This paper will explore the development of machine translation from 2012 to 2022 with the help of CiteSpace visual analysis. It is found that the research hotspots around the topic of machine translation include post-translation editing, artificial intelligence and other aspects, and machine translation is gradually combined with other disciplines to form an interdisciplinary research model. Therefore, in the future development, we should cultivate talents in multiple fields to promote the technological innovation of machine translation.