汉维神经机器翻译的探索

Gulnigar Mahmut, Mewlude Nijat, Rehmutulla Memet, A. Hamdulla
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引用次数: 2

摘要

现在,说不同语言的两个人可以通过实时翻译软件进行交流。这得益于机器翻译技术。在中国,有多种多样的语言。维吾尔语和汉语是中国新疆维吾尔自治区的官方语言,这使得提高汉维机器翻译的质量迫在眉睫。近年来,神经机器翻译(NMT)对大多数语言对都取得了可喜的成果。因此,在这项工作中,我们首先简要分析了维吾尔语机器翻译的难点。然后分别用统计框架(PBMT)和两种神经网络框架(NMT和M-NMT)研究汉维机器翻译的性能。因此,我们不仅对汉维机器翻译有了更好的了解,而且得到了我们的基线系统。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Exploration of Chinese-Uyghur neural machine translation
Nowadays two people who speak different languages are able to communicate with real-time translation software. This is benefited from machine translation technology. In China, there are multiple languages with great diversity. Uyghur and Chinese are the official languages of Xinjiang Uyghur Autonomous Region, China, which makes it urgent to improve the quality of Chinese-Uyghur (Uyghur-Chinese) machine translation. Recently, Neural machine translation (NMT) has reached promising results for most language pairs. Therefore, in this work, we first briefly analyze the difficulties of Uyghur machine translation. And then study the performance of Chinese-Uyghur machine translation with a statistical framework (PBMT) and two neural network frameworks (NMT and M-NMT), respectively. As a result, we not only have a better understanding of Chinese-Uyghur machine translation but also get our baseline system.
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