Loss in Translation: Learning Bilingual Word Mapping with a Retrieval Criterion
Table 10: Impact on the alignment of the quality of the word vectors trained on the same corpora.
['[EMPTY]', 'without subword', 'with subword']
A2SS0SSS0Px1 Quality of the embedding model. In this experiment, we study the impact of the quality of the word vectors on the performance of word translation. For this purpose, we trained word vectors on the same Wikipedia data, using skipgram with and without subword information. Overall, we observe that using subword information improves the accuracy by a few points on all pairs.