The NYU-CUBoulder Systems forSIGMORPHON 2020 Task 0 and Task 2
Table 4: Results on the official development data for our low-resource experiment. Trm=Vanilla transformer, Trm-PG=Pointer-generator transformer, Baseline=neural transducer by Makarov and Clematide (2018).
['System', 'Trm', 'Trm-PG', 'Baseline']
S5SS3SSS0Px4 Results. For some languages, such as Chichicapan Zapotec, the difference is up to 14%. While the neural transducer achieves a higher accuracy, our model performs only 2.45% worse than this state-of-the-art model. We are also able to observe the use of the copy mechanism for copying of OOV characters in the test sets of some languages.