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

Alexandre Magueresse, Vincent Carles, Evan Heetderks
2020 arXiv   pre-print
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.
arXiv:2006.07264v1 fatcat:mx2vyj6j3vhxplezy2fclffud4