Morphological Processing of Low-Resource Languages: Where We Are and What's Next
Automatic morphological processing can aid downstream natural language processing
applications, especially for low-resource languages, and assist language documentation …
applications, especially for low-resource languages, and assist language documentation …
Tackling the low-resource challenge for canonical segmentation
Canonical morphological segmentation consists of dividing words into their standardized
morphemes. Here, we are interested in approaches for the task when training data is limited …
morphemes. Here, we are interested in approaches for the task when training data is limited …
Convolutional neural networks for low-resource morpheme segmentation: baseline or state-of-the-art?
A Sorokin - Proceedings of the 16th Workshop on Computational …, 2019 - aclanthology.org
We apply convolutional neural networks to the task of shallow morpheme segmentation
using low-resource datasets for 5 different languages. We show that both in fully supervised …
using low-resource datasets for 5 different languages. We show that both in fully supervised …
Improving Morpheme Segmentation Using BERT Embeddings
A Sorokin - International Conference on Analysis of Images, Social …, 2021 - Springer
We offer a method of incorporating BERT embeddings into neural morpheme segmentation.
We show that our method significantly improves over baseline on 6 typologically diverse …
We show that our method significantly improves over baseline on 6 typologically diverse …