In this paper, we present a technique to use the information in multiple parallel speech streams, which are approximate translations of each other, in order to improve performance in a punctuation recovery task. We first build a phraselevel alignment of these multiple streams, using phrase tables to link the phrase pairs together. The information so collected is then used to make it more likely that sentence units are equivalent across streams. We applied this technique to a number of simultaneously interpreted speeches of the European Parliament Committees, for the recovery of the full stop, in four different languages (English, Italian, Portuguese and Spanish). We observed an average improvement in SER of 37% when compared to an existing baseline, in Portuguese and English.