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Proceedings of the 7th International Conference on Emerging Databases pp 111–118Cite as

A Study on Adjustable Dissimilarity Measure for Efficient Piano Learning

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Part of the Lecture Notes in Electrical Engineering book series (LNEE,volume 461)

Abstract

Recently, Kinect sensors have been used in many applications. Among them, there have been numerous studies that used Kinect sensors to improve efficiency of piano education. However, one of the main disadvantages of existing methods is that they did not take into consideration a dissimilarity measure that can occur when comparing the students’ and educator’s data. In addition, manually adjusting these settings can be cumbersome as for each case, there must be a set of optimal settings that match learner’s and educator’s data. In this paper, we propose a method to automatically set the piano learning stage by automatically adjusting the dissimilarity measure. Automatically adjusting the dissimilarity measure enables a gradual piano education and ultimately enhances the educational effect of the piano.

Keywords

  • Kinect sensor
  • Piano education
  • Dissimilarity measure

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Acknowledgement

This work was supported by Institute for Information & communications Technology Promotion (IITP) grant funded by the Korea government (MSIP) (No. R7120-17-1007, SIAT CCTV Cloud Platform).

Author information

Authors and Affiliations

  1. Department of IT Engineering, Sookmyung Women’s University, Seoul, South Korea

    So-Hyun Park & Young-Ho Park

  2. Department of Big Data Using Research Center, Sookmyung Women’s University, Seoul, South Korea

    Sun-Young Ihm

Authors
  1. So-Hyun Park
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  2. Sun-Young Ihm
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  3. Young-Ho Park
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Corresponding author

Correspondence to Young-Ho Park .

Editor information

Editors and Affiliations

  1. Department of Industrial Engineering, Inha University, Incheon, Korea (Republic of)

    Wookey Lee

  2. Department of Information and Communication Engineering, Inha University, Incheon, Korea (Republic of)

    Prof. Wonik Choi

  3. Department of Computer Science and Engineering, Sogang University, Seoul, Korea (Republic of)

    Prof. Sungwon Jung

  4. Department of Library and Information Science, Yonsei University, Seoul, Korea (Republic of)

    Prof. Min Song

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Park, SH., Ihm, SY., Park, YH. (2018). A Study on Adjustable Dissimilarity Measure for Efficient Piano Learning. In: Lee, W., Choi, W., Jung, S., Song, M. (eds) Proceedings of the 7th International Conference on Emerging Databases. Lecture Notes in Electrical Engineering, vol 461. Springer, Singapore. https://doi.org/10.1007/978-981-10-6520-0_12

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  • DOI: https://doi.org/10.1007/978-981-10-6520-0_12

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