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Morphological Processing of Low-Resource Languages: Where We Are and What's Next ...
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Dim Wihl Gat Tun: The Case for Linguistic Expertise in NLP for Underdocumented Languages ...
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Abstract:
Recent progress in NLP is driven by pretrained models leveraging massive datasets and has predominantly benefited the world's political and economic superpowers. Technologically underserved languages are left behind because they lack such resources. Hundreds of underserved languages, nevertheless, have available data sources in the form of interlinear glossed text (IGT) from language documentation efforts. IGT remains underutilized in NLP work, perhaps because its annotations are only semi-structured and often language-specific. With this paper, we make the case that IGT data can be leveraged successfully provided that target language expertise is available. We specifically advocate for collaboration with documentary linguists. Our paper provides a roadmap for successful projects utilizing IGT data: (1) It is essential to define which NLP tasks can be accomplished with the given IGT data and how these will benefit the speech community. (2) Great care and target language expertise is required when converting ...
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Keyword:
Computation and Language cs.CL; FOS Computer and information sciences
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URL: https://dx.doi.org/10.48550/arxiv.2203.09632 https://arxiv.org/abs/2203.09632
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Do RNN States Encode Abstract Phonological Alternations? ...
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SIGMORPHON 2020 Shared Task 0: Typologically Diverse Morphological Inflection ...
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Noise Isn't Always Negative: Countering Exposure Bias in Sequence-to-Sequence Inflection Models ...
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UniMorph 3.0: Universal Morphology
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In: Proceedings of the 12th Language Resources and Evaluation Conference (2020)
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Cross-Linguistic Syntactic Evaluation of Word Prediction Models ...
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The SIGMORPHON 2019 Shared Task: Morphological Analysis in Context and Cross-Lingual Transfer for Inflection ...
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Modeling Inflectional Complexity in Natural Language Processing
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