HCCL at SemEval-2017 Task 2: Combining Multilingual Word Embeddings and Transliteration Model for Semantic Similarity

Junqing He, Long Wu, Xuemin Zhao, Yonghong Yan
2017 Proceedings of the 11th International Workshop on Semantic Evaluation (SemEval-2017)  
In this paper, we introduce an approach to combining word embeddings and machine translation for multilingual semantic word similarity, the task2 of SemEval-2017. Thanks to the unsupervised transliteration model, our cross-lingual word embeddings encounter decreased sums of OOVs. Our results are produced using only monolingual Wikipedia corpora and a limited amount of sentence-aligned data. Although relatively little resources are utilized, our system ranked 3rd in the monolingual subtask and can be the 6th in the cross-lingual subtask.
doi:10.18653/v1/s17-2033 dblp:conf/semeval/HeWZY17 fatcat:e66q7na3nbdwbprczhlkcld5nu