• A
  • A
  • A
  • АБВ
  • АБВ
  • АБВ
  • A
  • A
  • A
  • A
  • A
Обычная версия сайта
  • RU
  • EN
  • HSE University
  • Publications
  • Book chapter
  • Functional models of elementary discursive units in Russian eSports commentary
  • RU
  • EN
Расширенный поиск
Высшая школа экономики
Национальный исследовательский университет
Priority areas
  • business informatics
  • economics
  • engineering science
  • humanitarian
  • IT and mathematics
  • law
  • management
  • mathematics
  • sociology
  • state and public administration
by year
  • 2027
  • 2026
  • 2025
  • 2024
  • 2023
  • 2022
  • 2021
  • 2020
  • 2019
  • 2018
  • 2017
  • 2016
  • 2015
  • 2014
  • 2013
  • 2012
  • 2011
  • 2010
  • 2009
  • 2008
  • 2007
  • 2006
  • 2005
  • 2004
  • 2003
  • 2002
  • 2001
  • 2000
  • 1999
  • 1998
  • 1997
  • 1996
  • 1995
  • 1994
  • 1993
  • 1992
  • 1991
  • 1990
  • 1989
  • 1988
  • 1987
  • 1986
  • 1985
  • 1984
  • 1983
  • 1982
  • 1981
  • 1980
  • 1979
  • 1978
  • 1977
  • 1976
  • 1975
  • 1974
  • 1973
  • 1972
  • 1971
  • 1970
  • 1969
  • 1968
  • 1967
  • 1966
  • 1965
  • 1964
  • 1963
  • 1958
  • More
Subject
News
June 2, 2026
HSE Study Reveals Imbalance in the Generative AI Market
Researchers at HSE University analysed how effectively the global generative artificial intelligence market converts investment into real revenue, concluding that AI is currently developing faster than it is paying off. The results have been published in the journal Foresight and STI Governance.
June 2, 2026
Discovering Science through Russian Language: HSE Prep Year Students Present at International Conference in Kazan
On May 23, 2026, the V International Scientific and Practical Conference ‘Discovering the World of Science’ took place in Kazan at the Preparatory Faculty for International Students of Kazan Federal University. Four students of the HSE International Preparatory Year took part in the event: two delivered their presentations in person, while two participated online. Their work was supervised by Acting Director of the International Prep Year Irina Isaeva and lecturer Ekaterina Kozhemyakova.
May 25, 2026
HSE Scientists Train Neural Network to 'Hear' Faults in Electric Motors
Researchers at the AI and Digital Science Institute of the HSE Faculty of Computer Science have developed a new method—the Signature-Guided Data Augmentation (SGDA) framework—that achieves 99% accuracy in motor fault detection and 86% accuracy in fault classification. The application of this approach can reduce industrial equipment repair costs, minimise downtime, and improve production safety. The study results have been published in Engineering Applications of Artificial Intelligence.

 

Have you spotted a typo?
Highlight it, click Ctrl+Enter and send us a message. Thank you for your help!

Publications
  • Books
  • Articles
  • Chapters of books
  • Working papers
  • Report a publication
  • Research at HSE

?

Functional models of elementary discursive units in Russian eSports commentary

P. 335–351.
Микулинский А. Д.

The paper is devoted to the issue of the local structure modeling of the eSports commentary spoken genre on an example of the Dota 2 computer discipline. ESports commentary is a spontaneous and creative speech aimed at describing of what is happening on the computer-gaming field. The main factors that force us to study it are the high popularity, the influencing nature of speech, as well as the lack of scientific attention. A theoretical and methodological framework of the study contains the elements of the structural and cognitivediscursive approaches in linguistics. The key research methods are language modeling, analysis of the local discourse structure in the cognitive perspective and quantitative analysis with regard to the corpus-based approach. The statistics were calculated for the sample with the total volume of 41 minutes and 30 seconds. The speeches belong to 14 Russian eSports commentators; they were delivered in 2017-2019. As a result, we have obtained a set of relevant patterns that represent characteristics of typical elementary discursive units (syntagmas) in the Dota 2 eSports commentary. These include a quick pronouncing, boundary pauses absence, frequent nuclear accent presence and embodiment of nouns and verbs. One part of the statistics represents general features of the Russian spoken discourse and human consciousness (e. g. the frequent use of absolute pauses); the other part correlate with a specificity of the situation in which the commentary is produced (e. g. the frequent use of short structures).

Language: English
Full text
DOI
Text on another site
Keywords: комментаторыcommentatorsструктура дискурсаlanguage modelingfunctional modelфункциональная модельdiscourse structureкиберспортивный дискурсesports discourseязыковое моделирование

In book

Синергия языков и культур 2022: междисциплинарные исследования
Синергия языков и культур 2022: междисциплинарные исследования
St. Petersburg: -, 2023.
Similar publications
Стилистические приемы в киберспортивном комментарии Dota 2
Микулинский А. Д., В кн.: ИНОСТРАННЫЙ ЯЗЫК И МЕЖКУЛЬТУРНАЯ КОММУНИКАЦИЯ. Материалы XV Международной студенческой научно-практической конференции.: Томск: Томский государственный педагогический университет, 2021. С. 41–46.
The tropes and stylistic figures used by esports commentators during official broadcasts of Dota 2 tournaments are analyzed. It seems that previously the genre of esports commentary was not considered in this aspect. Due to the specificity of the game and the rigidity of the conditions, the commentators have to choose stylistic techniques that not only enhance ...
Added: May 12, 2024
Сравнительный анализ лексики киберспортивного комментатора и геймера Dota 2
Микулинский А. Д., Теоретические и прикладные аспекты изучения речевой деятельности 2021 Т. 14 № 7 С. 89–98
The article examines and compares the vocabulary of eSports commentators and gamers, performing the role of commentators. In contrast to the sports sphere, in eSports the border between the status of a player and a commentator is quite vague, and gamers have the opportunity to perform as commentators during broadcasts. As a result, the audience ...
Added: May 12, 2024
GroundHog: Dialogue Generation using Multi-Grained Linguistic Input
Chernyavskiy A., Ostyakova L., Ilvovsky D., , in: Proceedings of the 5th Workshop on Computational Approaches to Discourse (CODI 2024).: Association for Computational Linguistics, 2024. P. 149–160.
Recent language models have significantly boosted conversational AI by enabling fast and cost-effective response generation in dialogue systems. However, dialogue systems based on neural generative approaches often lack truthfulness, reliability, and the ability to analyze the dialogue flow needed for smooth and consistent conversations with users. To address these issues, we introduce GroundHog, a modified ...
Added: May 9, 2024
Unleashing the Power of Discourse-Enhanced Transformers for Propaganda Detection
Chernyavskiy A., Ilvovsky D., Nakov P., , in: Proceedings of the 18th Conference of the European Chapter of the Association for Computational Linguistics: (Volume 1: Long Papers).: Association for Computational Linguistics, 2024. P. 1452–1462.
Added: May 9, 2024
Multimodal Discourse Trees in Forensic Linguistics
Galitsky B., Ilvovsky D., Goncharova E., , in: Компьютерная лингвистика и интеллектуальные технологии: По материалам ежегодной международной конференции «Диалог». Вып. 22.Вып. 22.: [б.и.], 2023.
We extend the concept of a discourse tree (DT) in the discourse representation of text towards data of various forms and natures. The communicative DT to include speech act theory, extended DT to ascend to the level of multiple documents, entity DT to track how discourse covers various entities were defined previously in computational linguistics, we now proceed ...
Added: November 10, 2023
Transformer-based Multi-Party Conversation Generation using Dialogue Discourse Acts Planning
Alexander Chernyavskiy, Ilvovsky D., , in: Proceedings of the 24th Meeting of the Special Interest Group on Discourse and Dialogue.: Association for Computational Linguistics, 2023. P. 519–529.
Recent transformer-based approaches to multi-party conversation generation may produce syntactically coherent but discursively inconsistent dialogues in some cases. To address this issue, we propose an approach to integrate a dialogue act planning stage into the end-to-end transformer-based generation pipeline. This approach consists of a transformer fine-tuning procedure based on linearized dialogue representations that include special ...
Added: October 6, 2023
TAPE: Assessing Few-shot Russian Language Understanding
Taktasheva E., Shavrina T., Fenogenova A. et al., , in: Findings of the Association for Computational Linguistics: EMNLP 2022.: Association for Computational Linguistics, 2022. P. 2472–2497.
Recent advances in zero-shot and few-shot learning have shown promise for a scope of research and practical purposes. However, this fast-growing area lacks standardized evaluation suites for non-English languages, hindering progress outside the Anglo-centric paradigm. To address this line of research, we propose TAPE (Text Attack and Perturbation Evaluation), a novel benchmark that includes six ...
Added: September 22, 2023
Изменение позы в диалоге показывает смену темы, смену ролей участников и когнитивные трудности говорящего и слушающего
Vashpanova K., Nikolaeva Y., В кн.: Психология познания: речевая опосредованность и категоризация в современной когнитивной науке: сборник материалов Всероссийской научной конференции памяти Дж. С. Брунера. Ярославский государственный университет им. П. Г. Демидова 10–11 декабря 2021 г.: Филигрань, 2022. С. 50–54.
В исследовании показано, что участники коммуникации последовательно сопровождают сменой позы границы между значимыми фрагментами в диалоге, такими как смена темы, смена ролей говорящего и слушающего или поиск новой стратегии объяснения говорящим, если адресат сигнализирует о трудностях понимания. Что любопытно, такие смены позы наблюдаются и у говорящего, и у слушающего. Кроме этого, замечены различия между возрастными ...
Added: August 10, 2023
О структурно-функциональном моделировании процессов с выделенным субъектом управления
Mylnikov L., Научно-техническая информация. Серия 2: Информационные процессы и системы 2022 № 2 С. 9–20
Рассматривается разработка способа представления структурно-функциональных моделей организационных систем, описываемых множеством взаимодействующих процессов и подпроцессов, функционирующих в условиях неопределенности. Создание новой системы артефактов обусловлено необходимостью выделения субъекта управления в явном виде, совмещения дискретных и непрерывных процессов в рамках одной модели, а также оценки эффективности получаемых моделей. Основой для этой разработки послужили методологии структурного моделирования eEPC, BPMN, IDEF. ...
Added: February 1, 2023
Correcting Texts Generated by Transformers using Discourse Features and Web Mining
Chernyavskiy A., Ilvovsky D., Galitsky B., , in: Proceedings of the Student Research Workshop Associated with RANLP 2021.: INCOMA Ltd, 2021. P. 36–43.
Recent transformer-based approaches to NLG like GPT-2 can generate syntactically coherent original texts. However, these generated texts have serious flaws: global discourse incoherence and meaninglessness of sentences in terms of entity values. We address both of these flaws: they are independent but can be combined to generate original texts that will be both consistent and ...
Added: May 29, 2022
Improving Text Generation via Neural Discourse Planning
Alexander Chernyavskiy, , in: WSDM 2022 - Proceedings of the 15th ACM International Conference on Web Search and Data Mining.: Association for Computing Machinery (ACM), 2022. P. 1543–1544.
Recent Transformer-based approaches to NLG like GPT-2 can generate syntactically coherent original texts. However, these generated texts have serious flaws. One of them is a global discourse incoherence. We present an approach to estimate the quality of discourse structure. Empirical results confirm that the discourse structure of currently generated texts is inaccurate. We propose the ...
Added: May 29, 2022
Ad Astra or Astray: Exploring Linguistic Knowledge of Multilingual BERT through NLI Task
Tikhonova M., Mikhailov V., Dina Pisarevskaya et al., Natural Language Engineering 2022 P. 1–30
Recent research has reported that standard fine-tuning approaches can be unstable due to being prone to various sources of randomness, including but not limited to weight initialization, training data order, and hardware. Such brittleness can lead to different evaluation results, prediction confidences, and generalization inconsistency of the same models independently fine-tuned under the same experimental setup. ...
Added: May 21, 2022
DSNDM: Deep Siamese Neural Discourse Model with Attention for Text Pairs Categorization and Ranking
Chernyavskiy A., Ilvovsky D., , in: Proceedings of the First Workshop on Computational Approaches to Discourse.: Association for Computational Linguistics, 2020. P. 76–85.
In this paper, the utility and advantages of the discourse analysis for text pairs categorization and ranking are investigated. We consider two tasks in which discourse structure seems useful and important: automatic verification of political statements, and ranking in question answering systems. We propose a neural network based approach to learn the match between pairs ...
Added: November 18, 2020
Proceedings of the First Workshop on Computational Approaches to Discourse
Association for Computational Linguistics, 2020.
Added: November 18, 2020
Efficient Language Modeling with Automatic Relevance Determination in Recurrent Neural Networks
Kodryan M., Grachev A., Ignatov D. I. et al., , in: Proceedings of the 4th Workshop on Representation Learning for NLP (RepL4NLP-2019)Issue W19-43.: Association for Computational Linguistics, 2019. P. 40–48.
Reduction of the number of parameters is one of the most important goals in Deep Learning. In this article we propose an adaptation of Doubly Stochastic Variational Inference for Automatic Relevance Determination (DSVI-ARD) for neural networks compression. We find this method to be especially useful in language modeling tasks, where large number of parameters in ...
Added: November 1, 2019
Compression of recurrent neural networks for efficient language modeling
Grachev A., Ignatov D. I., Savchenko A., Applied Soft Computing Journal 2019 Vol. 79 P. 354–362
Recurrent neural networks have proved to be an effective method for statistical language modeling. However, in practice their memory and run-time complexity are usually too large to be implemented in real-time offline mobile applications. In this paper we consider several compression techniques for recurrent neural networks including Long–Short Term Memory models. We make particular attention ...
Added: June 12, 2019
  • About
  • About
  • Key Figures & Facts
  • Sustainability at HSE University
  • Faculties & Departments
  • International Partnerships
  • Faculty & Staff
  • HSE Buildings
  • HSE University for Persons with Disabilities
  • Public Enquiries
  • Studies
  • Admissions
  • Programme Catalogue
  • Undergraduate
  • Graduate
  • Exchange Programmes
  • Summer University
  • Summer Schools
  • Semester in Moscow
  • Business Internship
  • Research
  • International Laboratories
  • Research Centres
  • Research Projects
  • Monitoring Studies
  • Conferences & Seminars
  • Academic Jobs
  • Yasin (April) International Academic Conference on Economic and Social Development
  • Media & Resources
  • Publications by staff
  • HSE Journals
  • Publishing House
  • iq.hse.ru: commentary by HSE experts
  • Library
  • Economic & Social Data Archive
  • Video
  • HSE Repository of Socio-Economic Information
  • HSE1993–2026
  • Contacts
  • Copyright
  • Privacy Policy
  • Site Map
Edit