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arXiv · 2201.11374

Systematic Investigation of Strategies Tailored for Low-Resource Settings for Low-Resource Dependency Parsing

Jivnesh Sandhan·Laxmidhar Behera·Pawan Goyal
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Abstract

In this work, we focus on low-resource dependency parsing for multiple languages. Several strategies are tailored to enhance performance in low-resource scenarios. While these are well-known to the community, it is not trivial to select the best-performing combination of these strategies for a low-resource language that we are interested in, and not much attention has been given to measuring the efficacy of these strategies. We experiment with 5 low-resource strategies for our ensembled approach on 7 Universal Dependency (UD) low-resource languages. Our exhaustive experimentation on these languages supports the effective improvements for languages not covered in pretrained models. We show a successful application of the ensembled system on a truly low-resource language Sanskrit. The code and data are available at: https://github.com/Jivnesh/SanDP

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Jivnesh Sandhan, Laxmidhar Behera, Pawan Goyal. 2022-01-27. Systematic Investigation of Strategies Tailored for Low-Resource Settings for Low-Resource Dependency Parsing. https://arxiv.org/abs/2201.11374

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