  Computational approaches in historical linguistics have been increasingly
applied during the past decade and many new methods that implement parts of the
traditional comparative method have been proposed. Despite these increased
efforts, there are not many easy-to-use and fast approaches for the task of
phonological reconstruction. Here we present a new framework that combines
state-of-the-art techniques for automated sequence comparison with novel
techniques for phonetic alignment analysis and sound correspondence pattern
detection to allow for the supervised reconstruction of word forms in ancestral
languages. We test the method on a new dataset covering six groups from three
different language families. The results show that our method yields promising
results while at the same time being not only fast but also easy to apply and
expand.
