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Adaptation of Classic Readability Metrics to Czech

Publication at Faculty of Mathematics and Physics |
2021

Abstract

We have fitted four classic readability metrics to Czech, using InterCorp (a parallel corpus with manual sentence alignment), CzEng 2.0 (a large parallel corpus of crawled web texts), and the optimize.curve fit algorithm from the SciPy library. The adapted metrics are: Flesch Reading Ease, Flesch-Kincaid Grade Level, Coleman-Liau Index, and Automated Readability Index.

We describe the details of the procedure and present satisfactory results. Besides, we discuss the sensitivity of these metrics to text paraphrases and correlation of readability scores with empirically observed reading comprehension, as well as the adaptation of Flesch Reading Ease to Czech from Russian.