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May 13, 2026
Immersion in Second Language Environment Influences Bilinguals Perception of Emotions
Researchers at the Cognitive Health and Intelligence Centre at the HSE Institute for Cognitive Neuroscience have discovered how bilingual individuals process emotional words in their native (first) and non-native (second) languages. It was found that the link between word meaning and bodily sensations is weaker in a second language than in a first language. However, the more a person is immersed in a language environment, the smaller this difference becomes. The article has been published in Language, Cognition and Neuroscience.
May 12, 2026
‘Any Real-Economy Company Can Use Our Products
The HSE Centre for Financial Research and Data Analytics combines fundamental and applied work, including in areas unique to Russia such as the connection between sentiment in the media and social networks and financial markets. The HSE News Service spoke with the centre’s director, Professor Tamara Teplova, about its work.
May 7, 2026
Researchers Find More Effective Approach to Revealing Majorana Zero Modes in Superconductors
An international team of researchers, including physicists from HSE MIEM, has demonstrated that nonmagnetic impurities can help more accurately reveal Majorana zero modes—quantum states considered promising building blocks for quantum computing. The researchers found that these impurities shift the energy levels that typically obscure the Majorana signal, while leaving the mode itself largely unaffected, thereby making its spectral peak more distinct. The study has been published in Research.

 

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?

Semi-automated typical error annotation for learner English essays: Integrating frameworks

P. 35–41.
Kutuzov A. B., Kuzmenko E.

This paper proposes integration of three open source utilities: brat web annotation tool, Freeling suite of linguistic analyzers and Aspell spellchecker. We demonstrate how their combination can be used to pre-annotate texts in a learner corpus of English essays with potential errors and ease human annotators’ work. Spellchecker alerts and morphological analyzer tagging probabilities are used to detect students’ possible errors of most typical sorts. F-measure for the developed pre-annotation framework with regard to human annotation is 0.57, which already makes the system a substantial help to human annotators, but at the same time leaves room for further improvement.

Language: English
Full text
Text on another site
Keywords: natural language processinglearner corporaerror annotation
Publication based on the results of:
Corpus studies of language variation: from deviations to linguistic norm (2015)

In book

Proceedings of the 4th workshop on NLP for Computer Assisted Language Learning at NODALIDA 2015, Vilnius, 11th May, 2015
Issue 114. , Linköping University Electronic Press, 2015.
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