Papers with Language documentation

2 papers
Joint Word and Morpheme Segmentation with Bayesian Non-Parametric Models (2023.findings-eacl)

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Challenge: Language documentation often requires segmenting transcriptions of utterances into words and morphemes . a long tradition of nonparametric Bayesian models is used to handle these tasks .
Approach: They propose a Bayesian model for simultaneously segmenting utterances at two levels . they use two under-resourced languages to better understand the value of weak supervision .
Outcome: The proposed model can be used to identify language documents with weak supervision.
GlossLM: A Massively Multilingual Corpus and Pretrained Model for Interlinear Glossed Text (2024.emnlp-main)

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Challenge: Existing resources for standardized, easily accessible IGT data limit their applicability to linguistic research.
Approach: They compile the largest existing corpus of interlinear glossed text data from a variety of sources and use it to generate annotated text.
Outcome: The proposed model outperforms SOTA models on monolingual corpora by 6.6%.

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