We encourage the outputs of the common BLSTM to be language-agnostic by using language-adversarial training (Chen et al., 2016) inspired by domainadversarial training (Ganin et al., 2016;Bousmalis et al., 2016).
this objective encourages the BLStM layers and the embedding layers to learn linguistically general-purpose representations, which are also useful for specific downstream tasks (Rei, 2017).