A robust self-learning method for fully unsupervised cross-lingual mappings of word embeddings

ACL 2018 Mikel ArtetxeGorka LabakaEneko Agirre

Recent work has managed to learn cross-lingual word embeddings without parallel data by mapping monolingual embeddings to a shared space through adversarial training. However, their evaluation has focused on favorable conditions, using comparable corpora or closely-related languages, and we show that they often fail in more realistic scenarios... (read more)

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