The performance of IL is consistently better on all metrics, with substantial gains for Tepehua of 6.5% accuracy over the closest system (semiCRF) and 10.4% accuracy over PGNet.
we find a large gap between the emulated and the real low-resource scenarios: while accuracy is above 50% for all high-resource languages even with reduced amounts of training data, for Popoluca and Tepehua, our best model only obtains 37.4% and 28.4% accuracy, respectively.