Resumen de Translation inference through multi-lingual word embedding similarity
Kathrin Donandt, Christian Chiarcos
This paper describes our contribution to the Shared Task on Translation Inference across Dictionaries (TIAD-2019). In our approach, we construct a multi-lingual word embedding space by projecting new languages in the feature space of a language for which a pretrained em- bedding model exists. We use the similarity of the word embeddings to predict candidate translations. Even if our projection methodology is rather simplistic, our system outperforms the other participating sys- tems with respect to the F1 measure for the language pairs which we predicted.
