Similarity Attraction for Robot's Dialect in Language Learning Using Social Robots

Askarbek Pazylbekov, Daryn Kalym, Anuar Otynshin, Anara Sandygulova

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The gradual transition towards the Kazakh language in the Republic of Kazakhstan raises the emergence of applying new technologies for learning the language. Considering the fact that the Kazakh language has dialectal forms, it is important to investigate how these language features would affect the interaction with the synthesized speech of a robot or a computer program. This paper presents a preliminary study exploring the effect of dialectal language on the human-robot interaction in an education-oriented environment. Participants were involved in the interaction with two different robots with pre-programmed language dialectal patterns - South and non-South, to learn new vocabulary. Findings show that there is a low significance in correlation, however, it is suggested that a small sample size led to the obtained results.

Original languageEnglish
Title of host publicationHRI 2019 - 14th ACM/IEEE International Conference on Human-Robot Interaction
PublisherIEEE Computer Society
Pages532-533
Number of pages2
ISBN (Electronic)9781538685556
DOIs
Publication statusPublished - Mar 22 2019
Event14th Annual ACM/IEEE International Conference on Human-Robot Interaction, HRI 2019 - Daegu, Korea, Republic of
Duration: Mar 11 2019Mar 14 2019

Publication series

NameACM/IEEE International Conference on Human-Robot Interaction
Volume2019-March
ISSN (Electronic)2167-2148

Conference

Conference14th Annual ACM/IEEE International Conference on Human-Robot Interaction, HRI 2019
CountryKorea, Republic of
CityDaegu
Period3/11/193/14/19

Fingerprint

Robots
Human robot interaction
Computer program listings
Education

Keywords

  • education
  • human-robot interaction
  • language learning
  • social robots

ASJC Scopus subject areas

  • Artificial Intelligence
  • Human-Computer Interaction
  • Electrical and Electronic Engineering

Cite this

Pazylbekov, A., Kalym, D., Otynshin, A., & Sandygulova, A. (2019). Similarity Attraction for Robot's Dialect in Language Learning Using Social Robots. In HRI 2019 - 14th ACM/IEEE International Conference on Human-Robot Interaction (pp. 532-533). [8673232] (ACM/IEEE International Conference on Human-Robot Interaction; Vol. 2019-March). IEEE Computer Society. https://doi.org/10.1109/HRI.2019.8673232

Similarity Attraction for Robot's Dialect in Language Learning Using Social Robots. / Pazylbekov, Askarbek; Kalym, Daryn; Otynshin, Anuar; Sandygulova, Anara.

HRI 2019 - 14th ACM/IEEE International Conference on Human-Robot Interaction. IEEE Computer Society, 2019. p. 532-533 8673232 (ACM/IEEE International Conference on Human-Robot Interaction; Vol. 2019-March).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Pazylbekov, A, Kalym, D, Otynshin, A & Sandygulova, A 2019, Similarity Attraction for Robot's Dialect in Language Learning Using Social Robots. in HRI 2019 - 14th ACM/IEEE International Conference on Human-Robot Interaction., 8673232, ACM/IEEE International Conference on Human-Robot Interaction, vol. 2019-March, IEEE Computer Society, pp. 532-533, 14th Annual ACM/IEEE International Conference on Human-Robot Interaction, HRI 2019, Daegu, Korea, Republic of, 3/11/19. https://doi.org/10.1109/HRI.2019.8673232
Pazylbekov A, Kalym D, Otynshin A, Sandygulova A. Similarity Attraction for Robot's Dialect in Language Learning Using Social Robots. In HRI 2019 - 14th ACM/IEEE International Conference on Human-Robot Interaction. IEEE Computer Society. 2019. p. 532-533. 8673232. (ACM/IEEE International Conference on Human-Robot Interaction). https://doi.org/10.1109/HRI.2019.8673232
Pazylbekov, Askarbek ; Kalym, Daryn ; Otynshin, Anuar ; Sandygulova, Anara. / Similarity Attraction for Robot's Dialect in Language Learning Using Social Robots. HRI 2019 - 14th ACM/IEEE International Conference on Human-Robot Interaction. IEEE Computer Society, 2019. pp. 532-533 (ACM/IEEE International Conference on Human-Robot Interaction).
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