We focus on learning linear mappings to construct the common semantic space and adopt correlational neural networks (CorrNet) (Chandar et al., 2016;Rajendran et al., 2015) as the basic model.
to previous work which only exploited monolingual word semantics, we introduce multiple cluster-level alignments and design a new cluster consistent CorrNet to align both words and clusters.