Cross-lingual Projections between Languages from Different Families

Mo Yu, Tiejun Zhao, Yalong Bai, Hao Tian, Dianhai Yu

Abstract: Cross-lingual projection methods can benefit from resource-rich languages to improve performances of NLP tasks in resources-scarce languages. However, these methods confronted the difficulty of syntactic differences between languages especially when the pair of languages varies greatly. To make the projection method well-generalize to diverse languages pairs, we enhance the projection method based on word alignments by introducing target-language word representations as features and proposing a novel noise removing method based on these word representations. Experiments showed that our methods improve the performances greatly on projections between English and Chinese.