Dr Masha Kyuseva


Research Fellow A

Academic and research departments

School of Literature and Languages.

Biography

Areas of specialism

Typology; Morphology; Lexical semantics; Computational linguistics; Sign languages; Circassian languages

My qualifications

2020
PhD in Linguistics
University of Melbourne & University of Birmingham
2014
MA in Computational Linguistics
Higher School of Economics, Moscow
2012
BA in Linguistics
Moscow State University

Research

Research interests

Research projects

My publications

Publications

Kyuseva, M. (2021). Qualitative lexicon in Russian Sign Language from a typological perspective. In: E. Rakhilina, T. Reznikova (eds.), The Typology of Physical Qualities. Amsterdam: John Benjamins Publishing Company. In press.
View abstract
The paper describes several expressions of physical qualities (namely, sharp, blunt, old, thick- wide, and thin-narrow) in Russian Sign Language (RSL) from a lexical typological perspective. This is the first study to analyse a sign language from the standpoint of the MLexT framework. The results show that RSL structures the aforementioned domains on the same grounds as spoken languages. This finding strongly supports the hypothesis that lexical systems are cognitively motivated. At the same time, RSL exhibits a number of non-trivial lexicalization strategies, which are not accidental but can be explained by the fact that this language is produced in the visual modality.
Kyuseva, M., D. Ryzhova, and E. Parina. (2021). Methodology at work: semantic fields SHARP and BLUNT. In: E. Rakhilina, T. Reznikova (eds.), The Typology of Physical Qualities. Amsterdam: John Benjamins Publishing Company. In press.
View abstract
The chapter illustrates the frame-based methodology of lexical typological analysis through the comparison of the qualities sharp and blunt in 21 languages. We show that these qualities tend to be asymmetrical, with bluntness being negatively defined through sharpness. The two main oppositions found in the field are (1) the shape of a sharp object, and (2) the sense through which the quality is primarily experienced. The first opposition divides all objects into bladed (knives, etc.) and pointed (needles, etc.) ones; the second opposition contrasts touch with vision, and it further translates to the juxtaposition of function (, etc.) vs. shape (, etc.). We also find that these oppositions determine the semantic shifts developed by words denoting sharpness or bluntness and that the metaphoric patterns are consistent across languages.
sharp/blunt instrumentspointed/rounded features
Kimmelman, V., M. Kyuseva, Y. Lomakina, and D. Perova. (2017). On the notion of metaphor in sign languages: some observations based on Russian Sign Language. Sign Language & Linguistics, 2 (20), pp. 157-182.
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Metaphors in sign languages have been an important research topic in recent years, and Taub's (2001) model of metaphor formation in signs has been influential in the field. In this paper, we analyze metaphors in signs of cognition and emotions in Russian Sign Language (RSL) and argue for a modification of Taub's (2001) theory of metaphor. We demonstrate that metaphor formation in RSL uses a number of mechanisms: a concrete sign can acquire metaphorical meaning without change, a part of a sequential compound can acquire a metaphorical meaning, and a morpheme within a productive sign or a simultaneous compound can acquire a metaphorical meaning. All these processes have parallels in spoken languages, so we argue for a modality-independent model of metaphor formation where metaphorical mapping is divorced from iconicity.
Ryzhova, D., M. Kyuseva, and D. Paperno. (2016). Typology of Adjectives Benchmark for Compositional Distributional Models. In: Calzolari N. et al. (eds.) Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC 2016). Paris: ELRA
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In this paper we present a novel application of compositional distributional semantic models (CDSMs): prediction of lexical typology. The paper introduces the notion of typological closeness, which is a novel rigorous formalization of semantic similarity based on comparison of multilingual data. Starting from the Moscow Database of Qualitative Features for adjective typology, we create four datasets of typological closeness, on which we test a range of distributional semantic models. We show that, on the one hand, vector representations of phrases based on data from one language can be used to predict how words within the phrase translate into different languages, and, on the other hand, that typological data can serve as a semantic benchmark for distributional models. We find that compositional distributional models, especially parametric ones, perform way above non-compositional alternatives on the task.
Reznikova, T., E. Rakhilina, O. Karpova, T. Arkhangelskiy, M. Kyuseva, and D. Ryzhova. (2013). Polysemy Patterns in Russian Adjectives and Adverbs: a Corpus-Oriented Database. In: I. Kor Chanine (ed.), Current Studies in Slavic Languages. Philadelphia, Amsterdam: John Benjamins Publishing Company, pp. 313-322.
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The paper presents a research tool for studying semantic change and polysemy patterns in Russian adjectives and adverbs. It is based on a corpus analysis of high-frequency polysemous units.