In order to induce initial translation pairs, we rely on the framework of multilingual probabilistic topic modeling (MuPTM) (Boyd-Graber and Blei, 2009;De Smet and Moens, 2009;Mimno et al., 2009;Zhang et al., 2010), that does not require a bilingual lexicon, it operates with nonparallel data, and is able to produce highly confident translation pairs for high-frequency words (Mimno et al., 2009;Vulić and Moens, 2013).
results reveal that, contrary to conclusions from prior work, the seeding of the bootstrapping process has a heavy impact on the quality of the learned lexicons.