> For the complete documentation index, see [llms.txt](https://ai4commsci.gitbook.io/formosanbank/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://ai4commsci.gitbook.io/formosanbank/additional-resources/publications.md).

# Publications

One of the main goals of FormosanBank is to provide comprehensive data that advances researchers' work on Formosan languages. In this section, you will find some of the work that was possible because of FormosanBank; that is, research that utilized data from FormosanBank.

* Le Ferrand, É., Hauser, C. M. B., Hartshorne, J., & Prud’hommeaux, E. (2025). [Faithful transcription: Leveraging Bible recordings to improve ASR for endangered languages](https://aclanthology.org/2025.ijcnlp-short.28/). In *Proceedings of the 14th International Joint Conference on Natural Language Processing and the 4th Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics*, 333–342.
* Le Ferrand, É., Jiang, B., Hartshorne, J., & Prud’hommeaux, E. (2025). [That doesn’t sound right: Evaluating speech transcription quality in field linguistics corpora](https://aclanthology.org/2025.acl-short.49/). In *Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)*, 627–635.
* Scheppat, H., Hartshorne, J., Leddy, D., Le Ferrand, E., & Prudhommeaux, E. (2025). [Integrating diverse corpora for training an endangered language machine translation system](https://aclanthology.org/2025.computel-main.19/). In *Proceedings of the Eight Workshop on the Use of Computational Methods in the Study of Endangered Languages (ComputEL-8)*, 162–169.
* Tall, O., Le Ferrand, É., Hartshorne, J., & Prud'hommeaux, E. (2024). Reclaiming Archival Texts with User-Friendly OCR. Poster presented at the *9th International Conference on Language Documentation & Conservation (ICLDC9)*, Miami, Florida.
* Ferrand, Eric Le, Zoey Liu, Antti Arppe, and Emily Prud’hommeaux. (2024). [Are modern neural ASR architectures robust for polysynthetic languages?](https://aclanthology.org/2024.findings-emnlp.166/). In *Findings of the Association for Computational Linguistics: EMNLP 2024*, pages 2953–2963, Miami, Florida, USA. Association for Computational Linguistics.