  In this work we focus on the task of automatically extracting bilingual
lexicon for the language pair Spanish-Nahuatl. This is a low-resource setting
where only a small amount of parallel corpus is available. Most of the
downstream methods do not work well under low-resources conditions. This is
specially true for the approaches that use vectorial representations like
Word2Vec. Our proposal is to construct bilingual word vectors from a graph.
This graph is generated using translation pairs obtained from an unsupervised
word alignment method.
  We show that, in a low-resource setting, these type of vectors are successful
in representing words in a bilingual semantic space. Moreover, when a linear
transformation is applied to translate words from one language to another, our
graph based representations considerably outperform the popular setting that
uses Word2Vec.
