neural-dialogue-metrics/rouge
An implementation of ROUGE family metrics for automatic summarization.
This tool helps researchers and developers working with natural language processing evaluate the quality of automatically generated summaries or translations. You input two pieces of text: a reference (the 'correct' version) and a candidate (the machine-generated version). It outputs scores (recall, precision, and F-measure) that indicate how well the candidate text matches the reference.
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Use this if you need a reliable and fast Python-based method to automatically score the quality of text summarization or machine translation outputs against a reference, without relying on external Perl scripts.
Not ideal if you need a tool that handles text preprocessing like tokenization, stemming, or stopword removal for you.
Stars
24
Forks
4
Language
Perl
License
MIT
Category
Last pushed
Jan 07, 2023
Commits (30d)
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