Kvasirs/MILES
MILES is a multilingual text simplifier inspired by LSBert - A BERT-based lexical simplification approach proposed in 2018. Unlike LSBert, MILES uses the bert-base-multilingual-uncased model, as well as simple language-agnostic approaches to complex word identification (CWI) and candidate ranking.
This project helps you simplify complex words in text across 22 different languages, making content easier to understand for a broader audience. You provide text or a text file in a supported language, and it returns a version with simpler vocabulary. This tool is ideal for anyone who needs to adapt written content for readers with different language proficiencies or reading levels.
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Use this if you need to quickly make written content more accessible and easier to read by simplifying complex words, especially for multilingual audiences.
Not ideal if preserving the precise original meaning with perfect synonymous substitutions is critical, as simplified words might occasionally alter the text's nuance.
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Python
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Last pushed
May 03, 2021
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