@inproceedings{kriukova-etal-2025-ai,
title = "{AI} for Interlinearization and {POS}-tagging: Teaching Linguists to Fish",
author = "Kriukova, Olga and
Schmirler, Katherine and
Moeller, Sarah and
Lovick, Olga and
Genee, Inge and
Arppe, Antti and
Smith, Alexandra",
editor = "Lachler, Jordan and
Agyapong, Godfred and
Arppe, Antti and
Moeller, Sarah and
Chaudhary, Aditi and
Rijhwani, Shruti and
Rosenblum, Daisy",
booktitle = "Proceedings of the Eight Workshop on the Use of Computational Methods in the Study of Endangered Languages",
month = mar,
year = "2025",
address = "Honolulu, Hawaii, USA",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2025.computel-main.16/",
pages = "139--149",
abstract = {This paper describes the process and learn- ing outcomes of a three-day workshop on ma- chine learning basics for documentary linguists. During this workshop, two groups of linguists working with two Indigenous languages of North America, Blackfoot and D{\"e}n{\"e} Su ̨{\l}{\i}n{\'e}, became acquainted with machine learning prin- ciples, explored how machine learning can be used in data processing for under-resourced languages and then applied different machine learning methods for automatic morphologi- cal interlinearization and parts-of-speech tag- ging. As a result, participants discovered paths to greater collaboration between computer sci- ence and documentary linguistics and reflected on how linguists might be enabled to apply ma- chine learning with less dependence on experts.}
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%0 Conference Proceedings
%T AI for Interlinearization and POS-tagging: Teaching Linguists to Fish
%A Kriukova, Olga
%A Schmirler, Katherine
%A Moeller, Sarah
%A Lovick, Olga
%A Genee, Inge
%A Arppe, Antti
%A Smith, Alexandra
%Y Lachler, Jordan
%Y Agyapong, Godfred
%Y Arppe, Antti
%Y Moeller, Sarah
%Y Chaudhary, Aditi
%Y Rijhwani, Shruti
%Y Rosenblum, Daisy
%S Proceedings of the Eight Workshop on the Use of Computational Methods in the Study of Endangered Languages
%D 2025
%8 March
%I Association for Computational Linguistics
%C Honolulu, Hawaii, USA
%F kriukova-etal-2025-ai
%X This paper describes the process and learn- ing outcomes of a three-day workshop on ma- chine learning basics for documentary linguists. During this workshop, two groups of linguists working with two Indigenous languages of North America, Blackfoot and Dënë Su ̨łıné, became acquainted with machine learning prin- ciples, explored how machine learning can be used in data processing for under-resourced languages and then applied different machine learning methods for automatic morphologi- cal interlinearization and parts-of-speech tag- ging. As a result, participants discovered paths to greater collaboration between computer sci- ence and documentary linguistics and reflected on how linguists might be enabled to apply ma- chine learning with less dependence on experts.
%U https://aclanthology.org/2025.computel-main.16/
%P 139-149
Markdown (Informal)
[AI for Interlinearization and POS-tagging: Teaching Linguists to Fish](https://aclanthology.org/2025.computel-main.16/) (Kriukova et al., ComputEL 2025)
ACL
- Olga Kriukova, Katherine Schmirler, Sarah Moeller, Olga Lovick, Inge Genee, Antti Arppe, and Alexandra Smith. 2025. AI for Interlinearization and POS-tagging: Teaching Linguists to Fish. In Proceedings of the Eight Workshop on the Use of Computational Methods in the Study of Endangered Languages, pages 139–149, Honolulu, Hawaii, USA. Association for Computational Linguistics.