Python package for obfuscating profanities, appeared in Findings of ACL 2023.
See the paper for additional details:
Nozza, D., Hovy, D. "The State of Profanity Obfuscation in Natural Language Processing Scientific Publications". In Findings of the Association for Computational Linguistics: ACL 2023. Association for Computational Linguistics, 2023. https://aclanthology.org/2023.findings-acl.240/
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python3 setup.py install
You can obfuscate text as strings, eventually specifying the language:
import profanity_obfuscation as prof
obfuscator = prof.Prof()
obfuscator.obfuscate_string("puta mierda")
>> 'p*ta m*erda'
obfuscator.obfuscate_string("porca puttana","IT")
>> 'p*rca p*ttana'
Or passing text files (such as .tex):
with open("paper.tex", 'r') as file:
text = file.read()
obfuscated_text = obfuscator.obfuscate_string(text)
with open("paper_obfuscated.tex", 'w') as f:
f.write(obfuscated_text)
You can also use the library to reveal profanities from their obfuscated versions:
obfuscator.reveal_profanity("m*erda")
>> 'mierda'
- Free software: MIT license
- Documentation: https://profanity-obfuscation.readthedocs.io.
If you use this tool please cite the following paper:
@inproceedings{nozza-hovy-2023-state,
title = "The State of Profanity Obfuscation in Natural Language Processing Scientific Publications",
author = "Nozza, Debora and
Hovy, Dirk",
booktitle = "Findings of the Association for Computational Linguistics: ACL 2023",
month = jul,
year = "2023",
address = "Toronto, Canada",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2023.findings-acl.240",
pages = "3897--3909",
}
This package was created with Cookiecutter_ and the audreyr/cookiecutter-pypackage_ project template.