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  • HSE University Develops Tool for Assessing Text Complexity in Low-Resource Languages

HSE University Develops Tool for Assessing Text Complexity in Low-Resource Languages

An installation at the National Library of the Republic of Tatarstan celebrating the history of Tatar writing, featuring symbols from various alphabets

An installation at the National Library of the Republic of Tatarstan celebrating the history of Tatar writing, featuring symbols from various alphabets
© Wikimedia Commons

Researchers at the HSE Centre for Language and Brain have developed a tool for assessing text complexity in low-resource languages. The first version supports several of Russia’s minority languages, including Adyghe, Bashkir, Buryat, Tatar, Ossetian, and Udmurt. This is the first tool of its kind designed specifically for these languages, taking into account their unique morphological and lexical features.

According to the Institute of Linguistics of the Russian Academy of Sciences, 155 languages are spoken in Russia. Some of them are used by relatively small communities—for example, around 80,000 people speak Adyghe, while 250,000 to 350,000 people speak Buryat, Ossetian, and Udmurt. Other languages, such as Bashkir and Tatar, have more than one million native speakers. All of these languages hold official status in various republics of Russia, making it essential not only to preserve them but also to create conditions for their development, including opportunities for learning and use in education and science. 

In 2025, a Presidential Decree approving the Fundamentals of the State Language Policy of the Russian Federation was adopted. It affirms linguistic diversity and outlines a strategy for the development and practical use of the languages spoken by the peoples of Russia. One way to advance these goals is to create digital tools that make working with low-resource languages easier and more accessible.

A team of scientists at the HSE Centre for Language and Brain has developed an online text complexity calculator for quick and easy assessment of text difficulty in several minority languages, taking into account their linguistic features. The calculator is based on Textometr, a tool created by Antonina Laposhina and Maria Lebedeva for evaluating the complexity of Russian-language texts.

The calculator developed by psycholinguists at HSE University evaluates texts across several parameters: word length and frequency based on data from language corpora; the percentage of vocabulary covered by the frequency list (ie the share of words in the text that appear among the 5,000 most frequent words in the respective language); and the distribution of parts of speech within the text. In addition, the calculator considers factors such as lexical density and diversity, as well as the text's narrativity and descriptiveness.

The key innovation is the use of the Flesch Reading Ease formula, adapted separately for each language, making it possible to assess text complexity and readability more accurately. 

The Flesch score is based on the number of words, sentences, and syllables, but the original coefficients were developed for English and do not work well for structurally different languages—such as the polysynthetic Adyghe language, in which the average word is much longer. In a 2025 study, Uliana Petrunina and Nina Zdorova recalculated the formula’s coefficients specifically for Adyghe, which significantly improved the accuracy of the readability assessment.

Uliana Petrunina

'The parameters of our calculator are adapted to the structural features of each of the six low-resource languages of Russia, using text corpora as well as frequency and morphological analyses. We also adapted the classic Flesch Reading Ease score. As a result, the algorithm can be easily reconfigured for other low-resource languages, regardless of their typological characteristics,' explains Uliana Petrunina, Research Fellow at the HSE Centre for Language and Brain and one of the developers of the tool.

The tool will help create comparable stimulus materials for linguistic experiments and provide teachers with a resource for selecting high-quality educational materials by difficulty level. This solution represents an important contribution to the preservation and development of Russia’s minority languages and to supporting the country’s linguistic diversity. 

Nina Zdorova

'Our tool allows researchers and teachers to select materials based on their linguistic complexity, which is particularly important for research and education in languages with limited resources,' says Nina Zdorova, one of the creators of the tool.

Future versions are expected to include additional low-resource languages that are underrepresented in linguistics, both in Russia and beyond.

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