Papers with writing systems
Robust Neural Machine Translation for Abugidas by Glyph Perturbation (2024.eacl-short)
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| Challenge: | Neural machine translation systems are vulnerable when trained on limited data. |
| Approach: | They propose to add noise to the training phase to increase robustness of NMT systems trained on limited data. |
| Outcome: | The proposed training strategy overcomes noise and improves robustness for low-resource tasks for abugida glyphs. |
MiLiC-Eval: Benchmarking Multilingual LLMs for China’s Minority Languages (2025.findings-acl)
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| Challenge: | Large language models excel in high-resource languages but struggle with low-resourced languages . minority languages such as Tibetan, Uyghur, Kazakh, and Mongolian are marginalized in NLP research due to limited digital representation and the scarcity of training data. |
| Approach: | They propose a benchmark for minority languages in China that tracks the progress of large language models on low-resource languages. |
| Outcome: | The proposed benchmark focuses on underrepresented writing systems and syntax-intensive tasks. |
Extensions to Brahmic script processing within the Nisaba library: new scripts, languages and utilities (2022.lrec-1)
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| Challenge: | a brahmic script is used to record endangered languages such as Dogri and Bengali for low-resource languages such that do not require visual normalization. |
| Approach: | They propose to extend Brahmic script functionality within the Nisaba library of finite-state script normalization and processing utilities. |
| Outcome: | The proposed extensions extend coverage from the original ten scripts to an additional ten of South Asia and beyond, including some used to record endangered languages such as Dogri. |