The simplest mathematical models of text markup for voicing by an emotional robot

The simplest mathematical models of text markup for voicing by an emotional robot

Ekaterina V. Isaeva
PhD in Philological Sciences, Associate Professor, Perm State University (PSU), 15, ul. Bukireva, Perm, 614990, Russia, This email address is being protected from spambots. You need JavaScript enabled to view it., ORCID: 0000-0003-1048-7492

Oleg G. Pensky
Doctor of Technical Science, Professor, PSU, 15, ul. Bukireva, Perm, 614990, Russia, This email address is being protected from spambots. You need JavaScript enabled to view it., ORCID: 0000-0003-4367-6791


Received  November 10, 2023

Abstract
The field of mathematical modeling of speech is attracting more and more attention due to the increased role of interdisciplinary efforts aimed at making robots' speech more natural. At the same time, few researchers have addressed the problem of mathematical modeling of the emotional component of robot speech. The aim of this paper is to contribute to a methodology of emotional text markup for robotic text voicing. The approach is original in its attempt to combine mathematics, semiotics, psychology, text generation, and perception. The paper describes the simplest models of the «psychology» of emotional robots. Based on these models the methodology of the text markup for its automatic voicing is offered, thus for creation of emotional coloring of the voiced text it is offered to use emoticons existing in a global network of the Internet, which are graphic designation of emotions. In addition, we propose a mathematical model that calculates the emotional perception of the whole voiced text by the perceiver. As an example, we present a simple text markup case and calculate the final perception score of the voiced text. In this paper, for the first time, an optimization problem is formulated, which provides a solution for choosing the text markup that provides the greatest emotional perception score after the text voicing.

Key words
Mathematical model, robot, automatic text voicing, emotions, text markup, methodology, emoticons of the Internet.

EDN
YVMDGV

Bibliographic description
Isaeva, E.V. and Pensky, O.G. (2024), "The simplest mathematical models of text markup for voicing by an emotional robot", Robotics and Technical Cybernetics, vol. 13, no. 1, pp. 12-17, EDN: YVMDGV. (in Russian).

UDC identifier
519.769

References

  1. Kirkov, A.J. and Pavlovsky, V.E. (2014), “The system of tonal acoustic communication”, Robotics and Technical Cybernetics, vol. 2, no. 3, pp. 50-54. (in Russian).
  2. GeeksforGeeks (2022), “Converting Text to Speech in Java”, available at: https://www.geeksforgeeks.org/converting-text-speech-java/ (Accessed 3 October 2023).
  3. Bradeckaja, I.G. and Solov'eva, N.Ju. (2017), Ritorika: Praktikum [Rhetoric: Workshop], RGUP, Moscow, Russia. (in Russian).
  4. Savchuk, S.O. and Mahova, A.A. (2022), “Multimedia Poetic Corpus: Principles of Creation and Markup Features”, Proceedings of the V.V. Vinogradov Russian Language Institute, no. 2, pp. 33–147. (in Russian).
  5. Diprose, J. et al. (2017), “Designing an API at an appropriate abstraction level for programming social robot applications”, J Vis Lang Comput, Academic Press, vol. 39, pp. 22–40.
  6. Yao, F. and Wang, Y. (2020), “Domain-specific sentiment analysis for tweets during hurricanes (DSSA-H): A domain-adversarial neural-network-based approach”, Comput Environ Urban Syst. Pergamon,vol. 83, pp. 101522.
  7. Xiang, W. et al. 2016), “Odor emoticon: An olfactory application that conveys emotions”, Int J Hum Comput Stud, Academic Press, vol. 91, pp. 52–61.
  8. Hartmann, K. et al. (2012), “Describing Human Emotions Through Mathematical Modelling”, in: IFAC Proceedings Volumes, Elsevier, vol. 45, no. 2, pp. 463–468.
  9. Penskiy, O.G., Sharapov, Yu.A. and Oshchepkova, N.V. (2018), Matematicheskie modeli robotov s neabsoljutnoj pamjat'ju i prilozhenija modelej [Mathematical models of robots with non-absolute memory and applications of the models], Perm State National Research University, Perm, Russia. (in Russian).
  10. Penskiy, O.G. and Chernikov, K.V. (2011), “Mathematical models of "mental diseases" of robots’, Vestnik of Perm University. Mathematics. Mechanics. Informatics, Perm State National Research University, vol. 4, no. 8, pp. 48-52. (in Russian).
  11. Druzhinin, V.N. 2004), Jeksperimental'naja psihologija [Experimental Psychology], Piter, SPb, Russia. (in Russian).
  12. Smolyakov, N.S. (2022),”Designing, documenting, and developing an information system for effective planning of commercials airing”, Master's thesis, PGNIU, Perm, Russia. (in Russian).
  13. SYMBL, “Emoji emoticons and emotions”, available at:  https://symbl.cc/ru/emoji/smileys-and-emotion/ (Accessed 3 October 2023).
  14. Unicode, “Full Emoji List, v15.1”, available at: https://unicode.org/emoji/charts/full-emoji-list.html (Accessed 3 October 2023).
  15. Anisimova, S.I. (2019), “General properties of mathematical models of complex emotions of a robot”, Modern high technologies, Perm State National Research University, no. 8, pp. 9-13. (in Russian).
  16. Dragunsky, V. (2021), "Where is this seen, where is this heard...", Deniskiny rasskazy [Deniskin's stories], available at: http://www.planetaskazok.ru/dentalesdrag/deniskinyrasskazygdejetovidanogdejetoslyhano (Accessed 3 October 2023). (in Russian).
  17. Pensky, O.G. (2023), Prostejshie matematicheskie modeli duhovnyh processov v sociume [Simplest mathematical models of spiritual processes in society], Typography of LLC "Rizo-Expert", Perm, Russia. (in Russian).
  18. Anisimova, S.I. and Pensky, O.G. [2020], Vychislenie parametrov prostejshego vospitanija robotov [Calculation of parameters of the simplest robot training], Rospatent, Russia, pat. 2020611142 USA. (in Russian).