Learning Multilingual Word Embeddings inLatent Metric Space: A Geometric Approach
Table 6: Indirect translation: Precision@1 for BLI.
['[BOLD] Method', '[BOLD] fr-it-pt', '[BOLD] it-de-es', '[BOLD] es-pt-fr', '[BOLD] avg.']
We observe that GeoMMmulti outperforms pivoting methods (cmp and pip) built on top of MSF and Procrustes for all language pairs. It should be noted that pivoting may lead to cascading of errors in the solution, whereas learning a common embedding space jointly mitigates this disadvantage. This is reaffirmed by our observation that GeoMMmulti performs significantly better than GeoMM (cmp) and GeoMM (pip).