Papers by Caitlin Richter
Low-resource Post Processing of Noisy OCR Output for Historical Corpus Digitisation (L18-1)
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| Challenge: | 7.6% of the words in the original OCR text contain an error; fully manual correction would take thousands of hours due to the size of the corpus. |
| Approach: | They propose a post-processing system to efficiently correct OCR errors in a 2.7 million word Faroese corpus. |
| Outcome: | The proposed method reduces the word error rate to 1.3% with around 65 hours of human annotator work. |
Morphological Segmentation for Low Resource Languages (2020.lrec-1)
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Justin Mott, Ann Bies, Stephanie Strassel, Jordan Kodner, Caitlin Richter, Hongzhi Xu, Mitchell Marcus
| Challenge: | a new corpus of annotated morphological data is described for the DARPA LORELEI Program . the data is annotating 9 low resource languages and root information for 7 of the languages . |
| Approach: | This paper describes a new morphology resource created by Linguistic Data Consortium and the University of Pennsylvania for the DARPA LORELEI Program. |
| Outcome: | The annotated corpus provides a gold standard for unsupervised morphological segmenters and analyzers . the language-specific annotation guidelines were language-independent, but included morphology paradigms and other specifications. |