14 citations · 24 across the 12 of their papers we have counts for
15 papers · 1 filter
Multiple Sources are Better Than One: Incorporating External Knowledge in Low-Resource Glossing
Changbing Yang, Garrett Nicolai, Miikka Silfverberg
In this paper, we address the data scarcity problem in automatic data-driven glossing for low-resource languages by coordinating multiple sources of linguistic expertise. We supple…
Embedded Translations for Low-resource Automated Glossing
Changbing Yang, Garrett Nicolai, Miikka Silfverberg
We investigate automatic interlinear glossing in low-resource settings. We augment a hard-attentional neural model with embedded translation information extracted from interlinear…
An Investigation of Noise in Morphological Inflection
Adam Wiemerslage, Changbing Yang, Garrett Nicolai +2
With a growing focus on morphological inflection systems for languages where high-quality data is scarce, training data noise is a serious but so far largely ignored concern. We ai…
Understanding Compositional Data Augmentation in Typologically Diverse Morphological Inflection
Farhan Samir, Miikka Silfverberg
Data augmentation techniques are widely used in low-resource automatic morphological inflection to overcome data sparsity. However, the full implications of these techniques remain…
Yet Another Format of Universal Dependencies for Korean
Yige Chen, Eunkyul Leah Jo, Yundong Yao +4
In this study, we propose a morpheme-based scheme for Korean dependency parsing and adopt the proposed scheme to Universal Dependencies. We present the linguistic rationale that il…
Dim Wihl Gat Tun: The Case for Linguistic Expertise in NLP for Underdocumented Languages
Clarissa Forbes, Farhan Samir, Bruce Harold Oliver +4
Recent progress in NLP is driven by pretrained models leveraging massive datasets and has predominantly benefited the world's political and economic superpowers. Technologically un…