jasonwei20/eda_nlp

Data augmentation for NLP, presented at EMNLP 2019

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Implements four lightweight text editing operations—synonym replacement, random insertion, swap, and deletion—that leverage WordNet for vocabulary substitution without requiring external language models. Works directly with tab-separated label-sentence datasets and exposes configurable alpha parameters to control augmentation intensity per operation. Particularly effective on small datasets (N < 500), with performance gains demonstrated across five text classification benchmarks.

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Python

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Last pushed

Mar 19, 2023

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