ManNER & ManPOS: Pioneering NLP for Endangered Manchu Language

Sangah Lee, Sungjoo Byun, Jean Seo, Minha Kang

Abstract
We present pioneering research in the realm of Natural Language Processing (NLP) for the endangered Manchu language. Recognizing the critical importance of linguistic preservation, we experiment with three language models – BiLSTM-CRF, BERT, and mBERT – for Named Entity Recognition (NER) and Part-of-Speech (POS) tagging tasks. Given the limited digitized Manchu text available, we augment the data using GloVe embeddings for the pre-training of BERT-based models. Remarkably, all models demonstrated outstanding performance, achieving over 90% F1 score in both NER and POS tagging tasks. Our research not only marks the first application of NLP on Manchu and the inaugural use of BERT-based models for the language but also stands as the first endeavor to employ Manchu for NER and POS tagging. To foster further exploration and applications in the field, we make our fine-tuning dataset and models available to the public. Through this research, we aim to underscore the significance of NLP in the protection and revitalization of low-resource languages.
Anthology ID:
2024.lrec-main.961
Volume:
Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)
Month:
May
Year:
2024
Address:
Torino, Italia
Editors:
Nicoletta Calzolari, Min-Yen Kan, Veronique Hoste, Alessandro Lenci, Sakriani Sakti, Nianwen Xue
Venues:
LREC | COLING
SIG:
Publisher:
ELRA and ICCL
Note:
Pages:
11030–11039
Language:
URL:
https://aclanthology.org/2024.lrec-main.961
DOI:
Bibkey:
Cite (ACL):
Sangah Lee, Sungjoo Byun, Jean Seo, and Minha Kang. 2024. ManNER & ManPOS: Pioneering NLP for Endangered Manchu Language. In Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024), pages 11030–11039, Torino, Italia. ELRA and ICCL.
Cite (Informal):
ManNER & ManPOS: Pioneering NLP for Endangered Manchu Language (Lee et al., LREC-COLING 2024)
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PDF:
https://preview.aclanthology.org/dois-2013-emnlp/2024.lrec-main.961.pdf
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