In traditional studies on language evolution, scholars often emphasize the
importance of sound laws and sound correspondences for phylogenetic inference
of language family trees. However, to date, computational approaches have
typically not taken this potential into account. Most computational studies
still rely on lexical cognates as major data source for phylogenetic
reconstruction in linguistics, although there do exist a few studies in which
authors praise the benefits of comparing words at the level of sound sequences.
Building on (a) ten diverse datasets from different language families, and (b)
state-of-the-art methods for automated cognate and sound correspondence
detection, we test, for the first time, the performance of sound-based versus
cognate-based approaches to phylogenetic reconstruction. Our results show that
phylogenies reconstructed from lexical cognates are topologically closer, by
approximately one third with respect to the generalized quartet distance on
average, to the gold standard phylogenies than phylogenies reconstructed from
sound correspondences.

通过对十个不同语系的多样数据集和最先进的自动同源词和音序对照检测方法的建立，我们首次测试了基于音序对比与基于同源词对比的方法在语系重建中的性能，并发现从同源词重建的语系与黄金标准语系之间的拓扑距离平均上缩短了约三分之一。