基于同义词数据增强的汉越神经机器翻译方法

汉越平行语料库的资源稀缺,很大程度上影响了汉越机器翻译效果.数据增强是提升汉越机器翻译的有效途径,基于双语词典的词汇替换数据增强是当前较为流行的方法.由于汉语-越南语属于低资源语言对,双语词典难以获得,而通过单语词向量获取低频词的同义词较为容易.因此,提出一种基于低频词的同义词替换的数据增强方法.该方法利用小规模的平行...

A Chinese-Vietnamese neural machine translation method based on synonym data augmentation

The scarcity of resources in the Chinese-Vietnamese parallel corpus greatly affects the effect of Chinese-Vietnamese machine translation. Data enhancement is an effective way to improveChinese-Vietnamese machine translation. Bilingual dictionary-based vocabulary replacement and data enhancement is currently a more popular method. Since Chinese-Vietnamesebilingualism is a low-resource languages, bilingual dictionaries are difficult to obtain, and synonyms for low-frequency words are easier to obtain from monolingual word vectors. Therefore, we propose a data enhancement method based on synonym replacement of low-frequency words. This method uses a small-scale parallel corpus. Firstly, by learning monolingual word vectors, a synonym list of low-frequency words at one end is obtained. Then, low-frequency words are replaced with synonyms. Secondly, the language model is used to filter the replaced sentences. Finally, The filtered sentence is matched with the sentence in the language on the other side to obtain an extended parallel corpus. The experimental results of Chinese-Vietnamese translation experiments show that the proposed method achieves good results, and the extended method improves the BLEU value by 1.8 and 1.1, compared with the baseline and back translation methods.