text-perturbation 0.1.5

This project is about the NLP task for text perturbation using different methods.

Text Perturbation

This project is about the NLP task for text perturbation using different perturbation methods. There are around 11 different methods.

1. delete_random_word : deletes randomly words
2. replace_synonyms : replaces a word with a synonym
3. backtranslation: translates english to german and back to english
4. paraphrase_using_bart: paraphrase the sentence
5. replace_with_hypernyms: replaces a word with hypernym
6. random_german_word: replace random word with a german word
7. predict_masked_word: masks a word from the sentence, then predicts using MLM
8. misspelling: simple typoes
9. random_char_insertion: randomly inserion character in a word
10. random_char_swaps: swaps character in a word
11. ocr_augmentation: augment word same as ocr.

Example to text perturbation:

# Example
from text_perturbation import perturbation
text = "hello, how are you?"

perturbate = perturbation.Perturbate(text)
perturbated_text = perturbate.random_german_word()

print(f"originial::: {text}")
print(f"perturbated_text::: {perturbated_text}")

Note: Please ensure the nltk data is downloaded. If not, use the following code to download.

# Example installation command
>>> import nltk
>>> nltk.download()