SubmissionNumber#=%=#14
FinalPaperTitle#=%=#Experiments in multivariant natural language processing for Nahuatl
ShortPaperTitle#=%=#
NumberOfPages#=%=#12
CopyrightSigned#=%=#
JobTitle#==#
Organization#==#
Abstract#==#Linguistic variation is a complicating factor for digital language technologies. This is particularly true for languages that lack an official "standard" variety, including many regional and minoritized languages. In this paper, we describe a set of experiments focused on multivariant natural language processing for the Nahuatl, an indigenous Mexican language with a high level of linguistic variation and no single recognized standard variant. Using small (10k tokens), recently-published annotated datasets for two Nahuatl variants, we compare the performance of single-variant, cross-variant, and joint training, and explore how different models perform on a third Nahuatl variant, unseen in training. These results and the subsequent discussion contribute to efforts of developing low-resource NLP that is robust to diatopic variation. We share all code used to process the data and run the experiments.
Author{1}{Firstname}#=%=#Robert
Author{1}{Lastname}#=%=#Pugh
Author{1}{Username}#=%=#rpugh-ets
Author{1}{Email}#=%=#robert.pugh408@gmail.com
Author{1}{Affiliation}#=%=#Indiana University
Author{2}{Firstname}#=%=#Francis
Author{2}{Lastname}#=%=#Tyers
Author{2}{Username}#=%=#fmt
Author{2}{Email}#=%=#ftyers@prompsit.com
Author{2}{Affiliation}#=%=#Indiana University

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