2024 NAACL NAACL 2024

Highly Granular Dialect Normalization and Phonological Dialect Translation for Limburgish

Abstract

AbstractWe study highly granular dialect normalization and phonological dialect translation on Limburgish, a non-standardized low-resource language with a wide variation in spelling conventions and phonology. We find improvements to the traditional transformer by embedding the geographic coordinates of dialects in dialect normalization tasks and use these geographically-embedded transformers to translate words between the phonologies of different dialects. These results are found to be consistent with notions in traditional Limburgish dialectology.

🌉 Interdisciplinary Bridge — Deep Learning and Natural Language Processing
🧭 Keyword Pioneer — phonological mapping
🐝 Cross-Pollinator — Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Security & Privacy, Speech & Audio