Towards Fast Cognate Alignment on Imbalanced Data

AbstractCognate alignment models purport to enable decipherment, but their speed and need for clean data can make them unsuitable for realistic decipherment problems. We seek to draw attention to these shortcomings in the hopes that future work may avoid them, and we outline two techniques which begin to overcome the described problems.