2024 COLING COLING 2024

Improved Neural Word Segmentation for Standard Tibetan

Abstract

AbstractAs Tibetan is traditionally not written with word delimiters, various means of word segmentation are necessary to prepare data for downstream tasks. Neural word segmentation has proven a successful means of parsing Tibetan text, but current performance lags behind that of neural word segmenters in other languages, such as Chinese or Japanese, and even behind languages with relatively similar orthographic structures, such as Vietnamese or Thai. We apply methods that have proven useful for these latter two languages , in addition to Classical Tibetan, toward the development of a neural word segmenter with the goal of raising the peak performance of Tibetan neural word segmentation to a level comparable to that reached for orthographically similar languages.

🧭 Keyword Pioneer — tibetan language
🐝 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

Authors