Comparison between random and daily speech database in the speech visualization

Nur Syafikah Binti Samsudin, Kazunori Mano

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

Abstract

This paper presents a new technique using animated texts as the speech features' visualization medium for checking and detecting language learners' pronunciation. The proposed visualization tool will transform learners' speech features such as pitch, tempo or rhythm into animated texts form, and the mispronounce parts can be located by comparing them with the correct sample. In our previous experiments, Japanese language learners gave positive feedback on the animated texts designs as their speech visualization tool. By practicing this tool, learners found that the mispronounce parts in their speech can be detected and confirmed easily. However, in order to have more practical feedback and response from the learners, besides using the plain speech data set, which only express random speech contents, the daily conversation speech data set is proposed as the data sample. In this paper, the comparison between both database samples for determining the proposed visualization tool's approachability was observed. Evaluation experiments results showed that participants gave positive responses to the animated texts visualization tool and were able to understand speech features in the visualized texts form better by using the daily conversation as the speech sample.

Original languageEnglish
Title of host publication2017 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages3135-3140
Number of pages6
Volume2017-January
ISBN (Electronic)9781538616451
DOIs
Publication statusPublished - 2017 Nov 27
Event2017 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2017 - Banff, Canada
Duration: 2017 Oct 52017 Oct 8

Other

Other2017 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2017
CountryCanada
CityBanff
Period17/10/517/10/8

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Keywords

  • Animated texts
  • Language learning
  • Nonlinguistic features
  • Paralinguistic features
  • Speech prosody
  • Speech visualization

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications
  • Human-Computer Interaction
  • Control and Optimization

Cite this

Samsudin, N. S. B., & Mano, K. (2017). Comparison between random and daily speech database in the speech visualization. In 2017 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2017 (Vol. 2017-January, pp. 3135-3140). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SMC.2017.8123109