Neural Models for Predicting Celtic Mutations

Published in Proceedings of the 1st Joint SLTU and CCURL Workshop at LREC 2020, Marseille, France, 11–12 May 2020, 2020

Recommended citation: Kevin P. Scannell. Neural Models for Predicting Celtic Mutations. 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 1–8, 2020.

The in-person conference was cancelled because of COVID-19.

Abstract: The Celtic languages share a common linguistic phenomenon known as initial mutations; these consist of pronunciation and spelling changes that occur at the beginning of some words, triggered in certain semantic or syntactic contexts. Initial mutations occur quite frequently and all non-trivial NLP systems for the Celtic languages must learn to handle them properly. In this paper we describe and evaluate neural network models for predicting mutations in two of the six Celtic languages: Irish and Scottish Gaelic. We also discuss applications of these models to grammatical error detection and language modeling.