What is data augmentation for text data?

What is data augmentation for text data?

Data augmentation for text data involves techniques to artificially expand the size of a text dataset by creating modified versions of existing data.

Can you give me some examples of data augmentation techniques?

Sure! Common techniques include synonym replacement, random insertion, random deletion, and back-translation.

How does back-translation work?

Back-translation involves translating text to another language and then translating it back to the original language, which can create variations.

What are the benefits of using data augmentation?

Benefits include improved model robustness, better generalization, and reduced overfitting by providing more diverse training examples.