However, while accuracy in emulated low-resource scenarios is over 50% for all languages, for the truly lowresource languages Popoluca and Tepehua, our best model only obtains 37.4% and 28.4% accuracy, respectively.
we conclude that canonical segmentation is still a challenging task for low-resource languages.