# Morphological Disambiguation of South S'ami with FSTs and Neural Networks

arXiv: https://arxiv.org/abs/2004.14062 · HTML: https://mlsanity.com/paper/2004.14062/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 29 Apr 2020.

## Built on by (most cited first, 2 of 2)

- [From Plenipotentiary to Puddingless: Users and Uses of New Words in Early English Letters](https://mlsanity.com/paper/2103.09926/) (2021)
- [Apurin~a Universal Dependencies Treebank](https://mlsanity.com/paper/2106.03391/) (2021)

## Abstract (arXiv)

We present a method for conducting morphological disambiguation for South S'ami, 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 S'ami UD Treebank and some synthetically generated South S'ami data. The disambiguation is done on the level of morphological tags ignoring word forms and lemmas; this makes it possible to use North S'ami training data for South S'ami without the need for a bilingual dictionary or aligned word embeddings. Our approach requires only minimal resources for South S'ami, which makes it usable and applicable in the contexts of any other endangered language as well.