Morphological Disambiguation of South Sámi with FSTs and Neural Networks

Mika Hämäläinen, Linda Wiechetek


Abstract
We present a method for conducting morphological disambiguation for South Sámi, which is an endangered language. Our method uses an FST-based morphological analyzer to produce an ambiguous set of morphological readings for each word in a sentence. These readings are disambiguated with a Bi-RNN model trained on the related North Sámi UD Treebank and some synthetically generated South Sámi data. The disambiguation is done on the level of morphological tags ignoring word forms and lemmas; this makes it possible to use North Sámi training data for South Sámi without the need for a bilingual dictionary or aligned word embeddings. Our approach requires only minimal resources for South Sámi, which makes it usable and applicable in the contexts of any other endangered language as well.
Anthology ID:
2020.sltu-1.5
Volume:
Proceedings of the 1st Joint Workshop on Spoken Language Technologies for Under-resourced languages (SLTU) and Collaboration and Computing for Under-Resourced Languages (CCURL)
Month:
May
Year:
2020
Address:
Marseille, France
Editors:
Dorothee Beermann, Laurent Besacier, Sakriani Sakti, Claudia Soria
Venue:
SLTU
SIG:
Publisher:
European Language Resources association
Note:
Pages:
36–40
Language:
English
URL:
https://aclanthology.org/2020.sltu-1.5
DOI:
Bibkey:
Cite (ACL):
Mika Hämäläinen and Linda Wiechetek. 2020. Morphological Disambiguation of South Sámi with FSTs and Neural Networks. In Proceedings of the 1st Joint Workshop on Spoken Language Technologies for Under-resourced languages (SLTU) and Collaboration and Computing for Under-Resourced Languages (CCURL), pages 36–40, Marseille, France. European Language Resources association.
Cite (Informal):
Morphological Disambiguation of South Sámi with FSTs and Neural Networks (Hämäläinen & Wiechetek, SLTU 2020)
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PDF:
https://aclanthology.org/2020.sltu-1.5.pdf