This paper discusses experiments that measure the effectiveness of machine-aided annotation for language documentation using both active learning simulation experiments and annotation experiments which involve actual documentary linguists interacting with machine example selection and label suggestion.
we deal with the task of labeling morphemes of the Mayan language Uspanteko with fine-grained parts-ofspeech.