  West Greenlandic, known by native speakers as Kalaallisut, is an extremely
low-resource polysynthetic language spoken by around 56,000 people in
Greenland. Here, we attempt to finetune a pretrained Kalaallisut-to-English
neural machine translation (NMT) system using web-crawled pseudoparallel
sentences from around 30 multilingual websites. We compile a corpus of over
93,000 Kalaallisut sentences and over 140,000 Danish sentences, then use
cross-lingual sentence embeddings and approximate nearest-neighbors search in
an attempt to mine near-translations from these corpora. Finally, we translate
the Danish sentence to English to obtain a synthetic Kalaallisut-English
aligned corpus. Although the resulting dataset is too small and noisy to
improve the pretrained MT model, we believe that with additional resources, we
could construct a better pseudoparallel corpus and achieve more promising
results on MT. We also note other possible uses of the monolingual Kalaallisut
data and discuss directions for future work. We make the code and data for our
experiments publicly available.
