Text augmentation

Part 1 (2020)
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Can anybody give some insights into the current text augmentation techniques in practice.

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@darek.kleczek won a Kaggle competition by adapting some computer vision augmentations to text:

Hopefully this is helpful.

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Yes, that’s creative to extrapolate image augmentation techniques to text :smiley:

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There are a couple of text augmentation techniques I heard of ( I did not implement these techniques myself yet):

  • Shuffle your text
  • Train a word2vec embedding, and use this to alter your text with synonyms.
  • Translate your text to another language and then translate it back to your original language.

Perhaps you can combine several techniques. Hopefully this helps :slight_smile:

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This provides a good survey on Data Augmentation.
Data Augmentation Approaches in Natural Language Processing: A Survey

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Those were helpful!

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  1. Replace a few words with their synonyms.
  2. Replace a few words with words that have similar (based on cosine similarity) word embeddings (like word2vec or GloVe) to those words.
  3. Replace words based on the context using powerful transformer models (BERT).