A Multi-Pairwise Extension of Procrustes Analysis for Multilingual Word Translation

In this paper we present a novel approach to simultaneously representing multiple languages in a common space. Procrustes Analysis (PA) is commonly used to find the optimal orthogonal word mapping in the bilingual case. The proposed Multi Pairwise Procrustes Analysis (MPPA) is a natural extension of the PA algorithm to multilingual word mapping. Unlike previous PA extensions that require a k-way dictionary, this approach requires only pairwise bilingual dictionaries that are much easier to construct in either a supervised or an unsupervised way. The improved performance of the MPPA algorithm is demonstrated on two standard multilingual tasks.