To Augment or Not to Augment? A Comparative Study on Text Augmentation Techniques for Low-Resource NLP
AbstractData-hungry deep neural networks have established themselves as the de facto standard for many NLP tasks, including the traditional sequence tagging ones. Despite their state-of-the-art performance on high-resource languages, they still fall behind their statistical counterpa...
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| Format: | Article |
| Language: | English |
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The MIT Press
2022-01-01
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| Series: | Computational Linguistics |
| Online Access: | https://direct.mit.edu/coli/article/48/1/5/108844/To-Augment-or-Not-to-Augment-A-Comparative-Study |