This paper proposes a novel method for automatically acquiring multi-lingual lexica from non-parallel data and reports some initial experiments to prove the viability of the approach. Using established techniques for building mono-lingual vector spaces two independent semantic vector spaces are built from textual data. These vector spaces are related to each other using a small {\em reference word list} of manually chosen reference points taken from available bi-lingual dictionaries. Other words can then be related to these reference points first in the one language and then in the other. In the present experiments, we apply the proposed method to comparable but non-parallel English-German data. The resulting bi-lingual lexicon is evaluated using an online English-German lexicon as gold standard. The results clearly demonstrate the viability of the proposed methodology.