Kazakh-Chinese neural machine translation based on data augmentation

Hao Wu; Beiqiang Ma

doi:10.1117/12.2674637

23 May 2023 Kazakh-Chinese neural machine translation based on data augmentation

Hao Wu, Beiqiang Ma

Proceedings Volume 12604, International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID 2022); 1260412 (2023) https://doi.org/10.1117/12.2674637
Event: 2nd International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID 2022), 2022, Guangzhou, China

Abstract

Machine translation is an important research field in natural language processing and artificial intelligence, which studies how to use computers to automatically convert languages. We experimented with attentional neural network machine translation for Chinese Kazakh language pairs and used data enhancement methods to alleviate the serious shortage of parallel corpus. The experimental results show that the proposed method is simple and effective, realize the mutual translation between Chinese and Kazakh with extremely low resources. At the same time, our proposed the method of two-way iterative back translation improves +4.47 BLEUs on Chinese to Kazakh and +5.97 BLEU on Kazakh to Chinese respectively.

Citation Download Citation

Hao Wu and Beiqiang Ma "Kazakh-Chinese neural machine translation based on data augmentation", Proc. SPIE 12604, International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID 2022), 1260412 (23 May 2023); https://doi.org/10.1117/12.2674637

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