Effective Cross-lingual Transfer of Neural Machine Translation Models without Shared Vocabularies
Table 3: Azerbaijani→English translation results with different types of pre-trained source embeddings.
['Pre-trained embedding', 'Bleu [%]']
We observe that monolingual embedding without a cross-lingual mapping also improves the transfer learning, but is significantly worse than our proposed embedding, i.e. mapped to the parent source (de) embedding. The target-mapped embedding is not compatible with the pre-trained encoder but directly guides the child model to establish the connection between the new source and the target. It also improves the system, but our method is still the best among the three embedding types.