Interdisciplinary Research in Conversation: A Case Study in Computational Morphology for Language Documentation
Enora Rice, Katharina von der Wense, Alexis Palmer
摘要
Computational morphology has the potential to support language documentation through tasks like morphological segmentation and the generation of Interlinear Glossed Text (IGT). However, our research outputs have seen limited use in real-world language documentation settings. This position paper situates the disconnect between computational morphology and language documentation within a broader misalignment between research and practice in NLP and argues that the field risks becoming decontextualized and ineffectual without systematic integration of User-Centered Design (UCD). To demonstrate how principles from UCD can reshape the research agenda, we present a case study of GlossLM, a stateof-the-art multilingual IGT generation model. Through a small-scale user study with three documentary linguists, we find that, despite strong metric-based performance, the system fails to meet core usability needs in real documentation contexts. These insights raise new research questions around model constraints, label standardization, segmentation, and personalization. We argue that centering users not only produces more effective tools, but surfaces richer, more relevant research directions.
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- IGT2P: From Interlinear Glossed Texts to ParadigmsSarah R. Moeller, Ling Liu, Changbing Yang, Katharina Kann 等EMNLP 2020 · 被引用 13 次
- Must NLP be Extractive?Steven BirdACL 2024 · 被引用 4 次
- Wav2Gloss: Generating Interlinear Glossed Text from SpeechTaiqi He, Kwanghee Choi, Lindia Tjuatja, Nathaniel R. Robinson 等ACL 2024 · 被引用 1 次
- GlossLM: A Massively Multilingual Corpus and Pretrained Model for Interlinear Glossed TextMichael Ginn, Lindia Tjuatja, Taiqi He, Enora Rice 等EMNLP 2024 · 被引用 1 次
- Multiple Sources are Better Than One: Incorporating External Knowledge in Low-Resource GlossingChangbing Yang, Garrett Nicolai, Miikka SilfverbergEMNLP 2024
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