Lunch at 12:30pm, (virtual) talk at 1pm, in 148 Fitzpatrick

Title: Towards explainable AI for Irish grammatical error correction

Abstract: Grammatical error correction is an important end-user application of natural language processing. In recent years, approaches using large language models have led to improved performance on this task, at least for English and a few other well-resourced languages. Nevertheless, it remains challenging to build systems that (1) provide results that are sufficiently reliable for end-users and (2) give some explanation for errors that they detect for the benefit of language learners. I will discuss recent progress on this problem for the Irish language, focusing on an important subset of errors involving the so-called “initial mutations” found in Irish and the other Celtic languages. The primary challenge is assembling a large enough dataset for training — we make use both synthetic data produced with the help of an Irish dependency parser, as well as error examples mined from Wikipedia edit logs.

Bio: Kevin Scannell is Professor of Mathematics and Computer Science at Saint Louis University, where he has taught since 1998. His main interest is the development of technology that helps speakers of indigenous and minority languages use their language online, with a particular focus on Irish and the other Celtic languages.