Abstract:
This paper describes the team ("Tamalli")’s
submission to AmericasNLP2021 shared task
on Open Machine Translation for low resource
South American languages. Our goal was to
evaluate different Machine Translation (MT)
techniques, statistical and neural-based, under
several configuration settings. We obtained
the second-best results for the language
pairs “Spanish-Bribri", “Spanish-Asháninka",
and “Spanish-Rarámuri" in the category “Development
set not used for training". Our performed
experiments will serve as a point of
reference for researchers working on MT with
low-resource languages.