  In this paper, we explore the use of convolutional networks (ConvNets) for
the purpose of cognate identification. We compare our architecture with binary
classifiers based on string similarity measures on different language families.
Our experiments show that convolutional networks achieve competitive results
across concepts and across language families at the task of cognate
identification.
