GlossAssist -- A Tool to Simplify Corpus Creation and Study the Effect of NLP Models in Low-Resource Documentation Settings
arXiv:2606.04367v1 Announce Type: new Abstract: Interlinear glossed text (IGT) is the standard format for linguistic annotation in language documentation. Producing it manually, however, is often slow and costly. Automated glossing systems have improved substantially in recent years, but adoption among field linguists remains limited. Existing tools are designed to be evaluated rather than used, offering no interpretable path for correction or the incorporation of linguistic expertise back into model behavior. We present GlossAssist, a glossing tool built around the retrieval-based architectur
The development of GlossAssist reflects a growing demand for practical, user-centric AI tools that integrate linguistic expertise into automated systems, moving beyond purely evaluative models.
This tool aims to simplify the creation of interlinear glossed text, addressing a critical bottleneck in language documentation, particularly for low-resource languages.
The focus on interpretable paths for correction and the incorporation of linguistic expertise differentiates GlossAssist from previous automated glossing systems, potentially increasing adoption among field linguists.
- · Field linguists
- · Language documentation projects
- · NLP researchers in low-resource settings
- · Developers of less adaptable or 'black box' automated glossing systems
The adoption of GlossAssist could significantly accelerate the annotation and study of low-resource languages.
Improved access to annotated data might foster the development of more robust NLP models for these languages, potentially broadening digital inclusion.
The methodology could inspire more human-in-the-loop AI tool development across various academic and specialized domains, emphasizing user control and expertise integration.
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