Related papers: Low-resource Languages: A Review of Past Work and Future Challenges

Low-resource Languages: A Review of Past Work and Future Challenges

URL: http://arxiv.org/abs/2006.07264v1
Date: Fri, 12 Jun 2020 15:21:57 GMT
Title: Low-resource Languages: A Review of Past Work and Future Challenges
Authors: Alexandre Magueresse, Vincent Carles, Evan Heetderks
Abstract summary: A current problem in NLP is massaging and processing low-resource languages which lack useful training attributes such as supervised data, number of native speakers or experts, etc. This review paper concisely summarizes previous groundbreaking achievements made towards resolving this problem, and analyzes potential improvements in the context of the overall future research direction.
Score: 68.8204255655161
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Abstract: A current problem in NLP is massaging and processing low-resource languages which lack useful training attributes such as supervised data, number of native speakers or experts, etc. This review paper concisely summarizes previous groundbreaking achievements made towards resolving this problem, and analyzes potential improvements in the context of the overall future research direction.

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