基于元嵌入的跨语言词嵌入方法研究

Research on Cross-Language Word Embedding Method Based on Meta-Embedding

跨语言词嵌入在自然语言处理任务中扮演着重要角色。现流行的跨语言词嵌入方法都基于一个同构假设,该假设认为不同语言的词嵌入空间具有相似的结构。然而,该同构假设在远距离语言对以及低资源上面临着巨大挑战。对此,提出对不同设置下的词嵌入进行融合创建元嵌入的方法提高跨语言词嵌入的质量。在EN-ZH上的实验结果表明,提出的元嵌入方法在跨语言词嵌入上的有效性。

Cross-language word embedding plays an important role in natural language processing tasks.The current popular cross-language word embedding methods are based on an isomorphism hypothesis,which assumes that word embedding spaces in different languages have similar structures.However,this isomorphic hypothesis faces huge challenges in terms of long-distance language pairs and low resources.In this regard,a method of fusing word embeddings under different settings to create meta-embedding is proposed to improve the quality of cross-language word embedding.The experimental results on EN-ZH show that the proposed meta-embedding method is effective in cross-language word embedding.