• A
  • A
  • A
  • ABC
  • ABC
  • ABC
  • А
  • А
  • А
  • А
  • А
Regular version of the site

HSE Develops App for Assessing Phonological Processing in Children

HSE Develops App for Assessing Phonological Processing in Children

© iStock

Researchers at the HSE Centre for Language and Brain have developed a new digital tool for assessing children's phonological processing skills—the ZARYA (Sound Analysis of the Russian Language) test battery. It is the first standardised application in Russia designed to provide a fast and reliable assessment of children's ability to distinguish speech sounds, retain them in working memory, and perform phonemic analysis. The app runs on Android tablets and smartphones and is available for download from RuStore. Details of the test validation have been published in the Journal of Speech, Language, and Hearing Research.

Phonological processing refers to the ability to distinguish speech sounds, retain them in working memory, retrieve them from long-term memory, and manipulate them in various ways. It is one of the fundamental mechanisms underlying the acquisition of both spoken and written language. Underdeveloped phonological skills can lead to persistent difficulties in learning to read and write, including dyslexia and dysgraphia. Early and accurate identification of phonological impairments makes it possible to begin intervention at an early stage and prevent more serious learning difficulties at school.

The ZARYA test battery was developed by combining the experience of international phonological assessments with the Russian neuropsychological tradition, in collaboration with the distinguished Russian neuropsychologist Tatiana Akhutina. Designed for children aged 5–12, the application integrates the latest scientific research with practical usability.

Svetlana Dorofeeva

Svetlana Dorofeeva

‘The ZARYA app is a convenient and reliable tool for assessing a child's ability to distinguish speech sounds, retain them in memory, and perform various sound-processing tasks. These skills are essential for the successful development of both spoken and written language. We created this tool for specialists working with children as well as researchers studying child language,’ said Svetlana Dorofeeva, Senior Research Fellow at the HSE Centre for Language and Brain.

The assessment consists of seven tasks of varying levels of difficulty, covering both speech comprehension and speech production. Together, they evaluate a child's ability to distinguish speech sounds in minimal contexts, retain phonological information in working memory, perform phonemic analysis, and manipulate phonemes. All test items are recorded by a professional voice actor, while the results are automatically compared with age-based norms, a feature that is essential for making accurate diagnostic decisions.

The application stores all participant responses, including audio recordings from speech-production tasks, allowing specialists to conduct detailed analyses and, where necessary, develop personalised intervention programmes. Results can also be exported as spreadsheets, making the tool particularly useful for research purposes.

ZARYA is intended for research centres investigating the development of speech and reading in Russian, as well as speech and language therapists, neuropsychologists, special educational needs specialists, university lecturers, and students in related fields. Thanks to its carefully designed structure, portability, and automated scoring system, the application improves both the quality and efficiency of diagnosing speech and reading disorders in children.

‘We evaluated the ZARYA test battery in several research studies. It is an evidence-based tool that demonstrates high inter-rater reliability. Every stimulus was selected according to a wide range of linguistic parameters rather than at random. The results do not depend on the examiner's pronunciation, the child's responses are preserved, and the system makes it possible to verify results and monitor progress over time,’ Svetlana Dorofeeva emphasised.

See also:

‘Hedgehog’ Versus ‘Relatives’: Researchers Measure How the Brain Responds to Unexpected Words During Natural Speech

Russian neurophysiologists, including researchers from HSE University, have demonstrated the feasibility of using event-related fields (ERFs) to study brain activity during natural speech perception. The researchers showed that this approach can be applied not only to individual words but also to continuous speech. Their findings indicate that words whose meanings differ significantly from the preceding context require longer processing times. The study also reveals that the brain processes function words in two stages: first, it identifies their grammatical role and then uses this information to predict the next word. The study has been published in Frontiers in Human Neuroscience.

HSE Researchers Create New Corpus of Early Child Speech in Russian

Researchers at the HSE Centre for Language and Brain have presented RusLan-M, an open multimedia corpus that makes it possible to trace the development of early child speech in Russian from first words to the emergence of complex grammatical constructions. The database contains around 41 hours of video recordings and more than 35,000 child utterances. The new resource will help researchers study more precisely how children acquire Russian and, in the longer term, develop more reliable tools for assessing speech development. The study has been published in Language Resources and Evaluation.

Scientists Develop Algorithm for More Reliable Processors in Data Centres

Researchers from HSE MIEM and Samara University have developed the LRF-3D algorithm to automatically bypass idle nodes in three-dimensional networks-on-chip. Thanks to its hierarchical architecture, the algorithm outperforms existing solutions in both speed and path accuracy, improving processor reliability for use in data centres, supercomputers, and AI computing. The source code and test results are publicly available.

Researchers Rank Recommendation Algorithms Using Sports Tournament Model

Researchers from the AI and Digital Science Institute at the HSE Faculty of Computer Science have developed an approach for selecting recommendation algorithms more effectively. Their approach uses pairwise comparisons of algorithms to create a tournament table, with the overall ranking based on their performance across all datasets in the tournament. This can reduce the number of algorithms that need to be tested when developing new services, saving both time and money. The study was presented at the 32nd ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2026).

Researchers Develop Method for Direct Generation of Regulatory DNA

Researchers at HSE University have developed a model for generating promoters and enhancers—DNA sequences that regulate gene activity. The model works directly with DNA nucleotides, without first transforming them into a continuous numerical representation. This solution could be useful for applications in synthetic biology and gene therapy. The study results were presented at the ICLR 2026 Workshop ‘Generative AI in Genomics (Gen^2): Barriers and Frontiers.’

Researchers at HSE University and Sber Train Neural Networks to Better Predict User Preferences

The HSE FCS AI and Digital Science Institute and Sber have introduced a new architecture for recommendation systems that combines two classes of models, enabling algorithms to better predict users’ interests and needs. A preprint of the paper has been published on arxiv.org and presented at Urban ML.

Social Integration: At the Crossroads of Knowledge and Values

The International Laboratory for Social Integration Research (ILSIR) at HSE University studies the challenges faced by vulnerable groups and explores ways to help them participate fully in everyday life. To develop effective solutions, the laboratory’s researchers combine cutting-edge methods with practical fieldwork. In this interview with the HSE News Service, Laboratory Head Elena Iarskaia-Smirnova discusses the laboratory’s work.

Physicists Discover What Happens Inside a Stable Vortex

Large vortices with characteristic spiral arms are often observed in the atmosphere and the ocean. Physicists from HSE University have explained how these structures form and why they retain their shape. The researchers found that velocities at points located along the same vortex arc remain correlated even over long distances. At the same time, this correlation weakens rapidly with increasing distance from the vortex centre. These differences help explain the formation of spiral arms and may improve models of atmospheric and oceanic currents. The findings have been published in Physical Review Fluids.

‘The Peak of Stupidity’ and ‘The Valley of Despair’: HSE Economists Propose an Explanation for the Dunning–Kruger Effect

The Dunning–Kruger effect, which describes a sharp surge in self-confidence among beginners followed by an equally rapid decline as they gain experience, can be explained by the nature of the learning process and the acquisition of new knowledge. This conclusion was reached by Andrey Vorchik of the HSE Faculty of Economic Sciences together with independent researcher Murat Mamyshev. They developed a mathematical model of learning and demonstrated how subjective confidence is formed and changes as knowledge accumulates, as well as how teachers can reduce the ‘valley of despair’ experienced by learners.

Toffee and Risk: Scientists Discover Why People Who Crave Sweets Make More Impulsive Choices

Having a sweet tooth may be linked not only to eating habits but also to the way people make decisions. Researchers at HSE University have found that people with a preference for sweet foods tend to behave more impulsively—not because they want immediate rewards, but because they are less willing to tolerate uncertainty. These findings may help improve treatments for addiction. The study findings have been published in Frontiers in Psychology.