ChrEn: Cherokee-English Machine Translation for Endangered Language Revitalization
Shiyue Zhang, Benjamin Frey, Mohit Bansal
摘要
Cherokee is a highly endangered Native American language spoken by the Cherokee people. The Cherokee culture is deeply embedded in its language. However, there are approximately only 2,000 fluent first language Cherokee speakers remaining in the world, and the number is declining every year. To help save this endangered language, we introduce ChrEn, a Cherokee-English parallel dataset, to facilitate machine translation research between Cherokee and English. Compared to some popular machine translation language pairs, ChrEn is extremely low-resource, only containing 14k sentence pairs in total. We split our parallel data in ways that facilitate both in-domain and out-of-domain evaluation. We also collect 5k Cherokee monolingual data to enable semi-supervised learning. Besides these datasets, we propose several Cherokee-English and English-Cherokee machine translation systems. We compare SMT (phrase-based) versus NMT (RNN-based and Transformer-based) systems; supervised versus semi-supervised (via language model, back-translation, and BERT/Multilingual-BERT) methods; as well as transfer learning versus multilingual joint training with 4 other languages. Our best results are 15.8/12.7 BLEU for in-domain and 6.5/5.0 BLEU for out-of-domain Chr-En/En-Chr translations, respectively, and we hope that our dataset and systems will encourage future work by the community for Cherokee language revitalization. 1
问问这篇 Paper
智能体会读完全文。
Lune 把这篇 Paper 索引到了每一个公式,引用它的顶会 Paper 也一样。你提问,回答直接引用原文。
引用它的顶会 Paper7
- How can NLP Help Revitalize Endangered Languages? A Case Study and Roadmap for the Cherokee LanguageShiyue Zhang, Benjamin Frey, Mohit BansalACL 2022 · 被引用 46 次
- Not always about you: Prioritizing community needs when developing endangered language technologyZoey Liu, Crystal Richardson, Richard J. Hatcher, Emily Prud'hommeauxACL 2022 · 被引用 36 次
- APNN-TC: accelerating arbitrary precision neural networks on ampere GPU tensor coresBoyuan Feng, Yuke Wang, Tong Geng, Ang Li 等SC 2021 · 被引用 36 次
- When Is Multilinguality a Curse? Language Modeling for 250 High- and Low-Resource LanguagesTyler A. Chang, Catherine Arnett, Zhuowen Tu, Ben BergenEMNLP 2024 · 被引用 12 次
- Dynamic Expert Specialization: Towards Catastrophic Forgetting-Free Multi-Domain MoE AdaptationJunzhuo Li, Bo Wang, Xiuze Zhou, Xuming HuEMNLP 2025 · 被引用 5 次
它引用的顶会 Paper1
相关 Paper
- Few-Shot Learning Translation from New LanguagesCarlos Mullov, Alexander WaibelEMNLP 2025
- Not Low-Resource Anymore: Aligner Ensembling, Batch Filtering, and New Datasets for Bengali-English Machine TranslationTahmid Hasan, Abhik Bhattacharjee, Kazi Samin, Masum Hasan 等EMNLP 2020 · 被引用 7 次
- ERNIE-M: Enhanced Multilingual Representation by Aligning Cross-lingual Semantics with Monolingual CorporaXuan Ouyang, Shuohuan Wang, Chao Pang, Yu Sun 等EMNLP 2021 · 被引用 68 次
- Neural Machine Translation with Phrase-Level Universal Visual RepresentationsQingkai Fang, Yang FengACL 2022
- Adapting High-resource NMT Models to Translate Low-resource Related Languages without Parallel DataWei-Jen Ko, Ahmed El-Kishky, Adithya Renduchintala, Vishrav Chaudhary 等ACL 2021
