A4 Vertaisarvioitu artikkeli konferenssijulkaisussa
Toxicity Detection in Finnish Using Machine Translation
Tekijät: Eskelinen Anni, Silvala Laura, Ginter Filip, Pyysalo Sampo, Laippala Veronika
Toimittaja: Tanel Alumäe, Mark Fishel
Konferenssin vakiintunut nimi: Nordic Conference on Computational Linguistics
Kustannuspaikka: Faroe Islands
Julkaisuvuosi: 2023
Journal: NEALT proceedings series
Kokoomateoksen nimi: The 24rd Nordic Conference on Computational Linguistics (NoDaLiDa 2023)
Sarjan nimi: NEALT Proceedings Series
Numero sarjassa: 52
Aloitussivu: 685
Lopetussivu: 695
ISBN: 978-99-1621-999-7
ISSN: 1736-8197
eISSN: 1736-6305
Verkko-osoite: https://aclanthology.org/2023.nodalida-1.68.pdf
Rinnakkaistallenteen osoite: https://research.utu.fi/converis/portal/detail/Publication/380758462
Due to the popularity of social media platforms and the sheer amount of usergenerated content online, the automatic detection of toxic language has become crucial in the creation of a friendly and safe digital space. Previous work has been mostly focusing on English leaving many lower-resource languages behind. In this paper, we present novel resources for toxicity detection in Finnish by introducing two new datasets, a machine translated toxicity dataset for Finnish based on the widely used English Jigsaw dataset and a smaller test set of Suomi24 discussion forum comments originally written in Finnish and manually annotated following the definitions of the labels that were used to annotate the Jigsaw dataset. We show that machine translating the training data to Finnish provides better toxicity detection results than using the original English training data and zero-shot cross-lingual transfer with XLM-R, even with our newly annotated dataset from Suomi24.
Ladattava julkaisu This is an electronic reprint of the original article. |