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A flexible solution to build text mining workflows that allows you to quickly combine Natural Language Processing tools from different sources.
Updated 30 months ago
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ochre
A tool to clean up text generated by OCR using individual words as well as their context.
2
mentions
1
contributor
What ochre can do for you
- Train character-based language models/LSTMs for OCR post-correction
- Ready to use workflows for data preprocessing, training correction models, doing the post-correction, and analyzing (remaining) errors
- Compare (corrected) OCR text to the gold standard based on character error rate (CER), word error rate (WER), and order independent word error rate
- Analyze OCR errors on the word level
- Discover OCR post-correction data sets
Ochre is experimental software for cleaning up text with OCR mistakes. The software was developed to investigate whether character-based language models can be used to remove OCR mistakes. In addition, ochre provides functionality to analyze the kinds of OCR mistakes in a corpus. This enables researchers to compare different OCR post-correction methods and find out what kinds of mistakes they are good at solving.
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Contact person
Janneke van der Zwaan
Netherlands eScience Center
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