PhD thesis proposal defense-Department of Computer Science-Steinþór Steingrímsson
Effectively Aligning and Filtering Parallel Corpora under Sparse Data Conditions
Monday the 29th of June 2020, Steinþór Steingrímsson will defend his PhD thesis proposal.
Candidate: Steinþór Steingrímsson
Supervisor: Dr. Hrafn
Loftsson, Associate Professor, Department of Computer Science, Reykjavik
University and Dr. Any Way, Professor, School of Computing, Dublin City
University
Title: Effectively Aligning and Filtering Parallel Corpora under Sparse Data Conditions
Date and Time: June 29th at 10:00 in Room M105
Abstract: Parallel corpora are key to developing good machine translation systems. However, abundant parallel data are hard to come by, especially for languages with a low number of speakers. When rich morphology exacerbates the data sparsity problem, it is imperative to have accurate alignment and filtering methods that can help make the most of what is available by maximising the number of correctly translated segments in a corpus and minimising noise by removing incorrect translations and segments containing extraneous data. This paper sets out a research plan for improving alignment and filtering methods for parallel texts in low-resource settings. We propose an effective unsupervised alignment method to tackle the alignment problem. Moreover, we propose a strategy to supplement state-of-the-art models with automatically extracted information using basic NLP tools to effectively handle rich morphology.
