Textometr: an online tool for automated complexity level assessment of texts for Russian language learners


Evaluation of text accessibility seems to be an extremely urgent and labor-consuming task in the process of preparing texts for teaching Russian as a foreign language. On the other hand, the procedure of assigning a text to one of the levels on the CEFR scale (from A1 to C2) is well-formalized and described in the professional literature, which opens opportunities for its automation. This paper presents Textometr - a new free web-based tool for estimating CEFR level and other key statistics from any given text in Russian that can be relevant for adapting it for foreign students. The automated assessment of the text level here is based on a regression model, trained on the dataset of more than 800 texts from Russian textbooks for foreigners, applying several machine learning and natural language processing methods. In addition to the CEFR level, the tool provides information relevant for adapting the text to educational tasks: lists of keywords and words for a potential vocabulary list, statistics on the text coverage by frequency lists and CEFR-graded vocabulary lists (lexical minima), a frequency list of the text, a forecast of the time needed for reading. The tool shortages at the current stage of development and suggested ways to solve them are also discussed. Finally, the results of the test on the tool quality and the vectors for its further development are reported. Textometr can provide helpful information not only to teachers and guidance teachers, but to authors of textbooks and publishers to check the compliance of the text content with the declared level and educational goals.

Full Text


Figure 1. Interface of Textometr

Figure 2. Average sentence length values by CEFR Level


Parameter values of the text from “Zhili-byli” textbook obtained by Textometr



Text level declared in the textbook


Predicted by Textometr level

A1. Elementary level



Unique words


Lexical diversity




Average sentence length



Крым, Ялта, поезд, Симферополь,
час, автобус, интересный, поездка

Most useful words

Берег, деревня, во-первых, купе, выбирать,
пешком, задание, через, во-вторых, домашний,
есть, самый, необычный, узнавать

Text coverage by A1 vocabulary list

87% of text

Words out of A1 vocabulary list

Во-первых, выбирать, ботанический, уютный, экспресс,
задание, купе, через, необычный, современность,
чудесный, деревня, пешком, во-вторых, ореанда,
самый, берег, домашний, городок, узнавать

Text coverage by A2 vocabulary list

92% of text

Words out of A2 vocabulary list

Современность, чудесный, во-первых, купе,
ботанический, уютный, экспресс, во-вторых,
ореанда, ну, необычный, городок, узнавать

Text coverage by B1 vocabulary list

95% of text

Words out of B1 vocabulary list

Современность, чудесный, купе, ботанический,
уютный, экспресс, ореанда, необычный, городок

Text coverage by B2 vocabulary list

98% of text

Words out of B2 vocabulary list

Современность, городок, ореанда, ботанический

Text coverage by C1 vocabulary list

98% of text

Words out of C1 vocabulary list

Городок, ореанда, ботанический

Text coverage by frequency list 5 000

96% of text

Useful words that are out of lexical minima


Rare words

Экспресс, ботанический, ореанда

Detail reading for details will take

7 min

Skimming reading will take

4 min

Possible grammar topics

Prepositional case

Frequency list of the text

В 13; мы 13; и 9; быть 6; на 6; я 5;
чаc 4; интересный 3; Крым 3; ...



About the authors

Antonina N. Laposhina

Pushkin State Russian Language Institute

Author for correspondence.
Email: ANLaposhina@pushkin.institute

leading expert, Laboratory of Cognitive and Linguistic Studies

6 Akademika Volgina St, Moscow, 117485, Russian Federation

Maria Yu. Lebedeva

Pushkin State Russian Language Institute

Email: MULebedeva@pushkin.institute

Candidate of Philology, leading researcher of the Laboratory of Cognitive and Linguistic Research, Associate Professor of the Department of Methods of Teaching Russian as a Foreign Language

6 Akademika Volgina St, Moscow, 117485, Russian Federation


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Supplementary files

Supplementary Files
1. Figure 1. Interface of Textometr

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2. Figure 2. Average sentence length values by CEFR Level

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Copyright (c) 2021 Laposhina A.N., Lebedeva M.Y.

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