Multilingual Dependency Parsing for Low-Resource Languages: Case Studies on North Saami and Komi-Zyrian

Kyungtae Lim (1) , Niko Partanen (1) , Thierry Poibeau (1)

1 Lattice - Lattice - Langues, Textes, Traitements informatiques, Cognition - UMR 8094

The paper presents a method for parsing low-resource languages with very small training corpora using multilingual word embeddings and annotated corpora of larger languages. The study demonstrates that specific language combinations enable improved dependency parsing when compared to previous work, allowing for wider reuse of pre-existing resources when parsing low-resource languages. The study also explores the question of whether contemporary contact languages or genetically related languages would be the most fruitful starting point for multilingual parsing scenarios.

Mots clés: dependency parsing; word embeddings; Uralic languages

Domaines: Traitement du texte et du document; Intelligence artificielle [cs.AI]; Apprentissage [cs.LG]; Informatique; Linguistique; Linguistique; Sciences de l'information et de la communication

Kyungtae Lim, Niko Partanen, Thierry Poibeau. Multilingual Dependency Parsing for Low-Resource Languages: Case Studies on North Saami and Komi-Zyrian. Language Resource and Evaluation Conference, ELRA, May 2018, Miyazaki, Japan. ⟨hal-01856178⟩