Research on Chinese-Tibetan Neural Machine Translation View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2018-10-07

AUTHORS

Wen Lai , Xiaobing Zhao , Xiaqing Li

ABSTRACT

At present, the research on Tibetan machine translation is mainly focused on Tibetan-Chinese machine translation and the research on Chinese-Tibetan machine translation is almost blank. In this paper, the neural machine translation model is applied to the Chinese-Tibetan machine translation task for the first time, the syntax tree is also introduced into the Chinese-Tibetan neural machine translation model for the first time, and a good translation effect is achieved. Besides, the preprocessing methods we use are syllable segmentation on Tibetan corpus and character segmentation on Chinese Corpus, which has a better performance than the word segmentation on both Chinese and Tibetan corpus. The experimental results show that performance of the neural network translation model based on the completely self-attention mechanism is the best in the Chinese-Tibetan machine translation task and the BLEU score is increased by one percentage point. More... »

PAGES

99-108

Book

TITLE

Chinese Computational Linguistics and Natural Language Processing Based on Naturally Annotated Big Data

ISBN

978-3-030-01715-6
978-3-030-01716-3

Author Affiliations

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-030-01716-3_9

DOI

http://dx.doi.org/10.1007/978-3-030-01716-3_9

DIMENSIONS

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