1 p.27 Fig. 1 Example of a koto score. [1] 1 1 [1] A 2. Rogers [4] Zhang [5] [6] [7] Löchtefeld [8] Xiao [

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1 1,a) , Evaluation of Koto Learning Support Method Considering Articulations Mayuka Doi 1,a) Homei Miyashita 1 Received: June 7, 2017, Accepted: December 8, 2017 Abstract: Koto players need not only to have play techniques but also to read koto scores and to understand string positions instantly. In addition, there are many articulations of the koto and there is no information about timing of switching fingers and pushing the string below in koto scores. In this paper, we propose a method to support learning how to play the koto including several articulations for beginners. The method is to present playing support information to strings and a plate of the koto directly. A system presents them by projection mapping. We considered the influence and effect of it on beginners. We also evaluated its effectiveness for an experienced person by comparative experiments. As a result of them, presentations of string positions, fingering, and some articulations are useful for beginners but it is not useful for experienced people. Keywords: koto, instrument learning, articulations, projection mapping *1 1 Meiji University, Nakano, Tokyo , Japan a) cs172030@meiji.ac.jp [1], [2], [3] *1 c 2018 Information Processing Society of Japan 912

2 1 p.27 Fig. 1 Example of a koto score. [1] 1 1 [1] A 2. Rogers [4] Zhang [5] [6] [7] Löchtefeld [8] Xiao [9] 7 [10] Raymaekers [11] c 2018 Information Processing Society of Japan 913

3 [12] [13] [14] [15] Table 1 1 Articulations and their presentation methods. c 2018 Information Processing Society of Japan 914

4 c 2018 Information Processing Society of Japan 915

5 Fig. 2 2 Our proposed method. 3 Fig. 3 A koto score (left) and an example of the presentation of the performance support information corresponding to it (right) Fig. 4 Presentation of Oshide. 2 4cm 3cm 1 4 (1) 4(2) c 2018 Information Processing Society of Japan 916

6 4(3) 4(4) =75 =72 =60 =48 = cm 2cm csv 5 Fig. 5 System structure. 4.4 PC NEC PC-LZ650NSS 6 QUMI VIVITEK QUMI Q5-RD PC Windows 10 Processing Pure Data 16 ms 1 5. * *2 c 2018 Information Processing Society of Japan 917

7 3 Table 3 The experiment schedule. 6 Fig. 6 Kinds of conditions. 2 Table 2 Music experience and allotment method of each participant I I P1 P T1 T5 3 =60 1sec P1 P6 3 7 T1 T t c 2018 Information Processing Society of Japan 918

8 T1 T5 T5 5% T1 T3 4 T2 T5 p <.10 T6 T7 T6 T7 T6 T5 T6 T7 T2 T2 T6 T2 p < P1 P Fig. 7 Judgement of errors. 9 P1 P6 Fig. 9 Time used for each method for each participant in P1 P6. 8 T1 T7 Fig. 8 Numbers of picking, fingering, and articulation errors in T1 T7. c 2018 Information Processing Society of Japan 919

9 4 T1 T7 Table 4 Performances delay time of each participant in T1 T7 (unit: beat). 11 P1 P6 Fig. 11 Motivation scores in P1 P6. 10 T1 T7 Fig. 10 Subjective performance evaluations in T1 T7. T6 T7 T6 2 T7 1 T1 T3 T7 T2 1 T5 T6 2 T3 T6 T7 10 T1 T2 T4 5% T3 p < P3 P6 P1 P2 P5 P T1 T5 T6 T7 T7 T6 T7 2 1 T6 b c a c 2018 Information Processing Society of Japan 920

10 T1 T5 T2 T6 T1 T7 P1 P2 2 T6 T7 T5 T5 T2 T3 f P Fig. 12 Numbers of picking and fingering errors. 5.1 I = % t p < c 2018 Information Processing Society of Japan 921

11 Table 5 Targeted articulations and their problems. 6 Table 6 Music experience and allotment method of each participant B ms 200 ms 200 ms =60 =48 = =60 4 = KORG CA c 2018 Information Processing Society of Japan 922

12 7 Table 7 Number of picking, fingering, articulation errors (unit: time) and performance delay time (unit: beat). 8 Table 8 Evaluations and results of Oshide. 9 Table 9 Evaluations and results of Tsukiiro % t c 2018 Information Processing Society of Japan 923

13 10 Table 10 Evaluations and results of Uraren j 3 c 2018 Information Processing Society of Japan 924

14 I OKOTO I = Fig. 13 The number of picking errors of before and after practice by experienced people. 1 =30 3 = c 2018 Information Processing Society of Japan 925

15 c 2018 Information Processing Society of Japan 926

16 [13], [15] Learning with Interactive Projection, Proc. ITS 14, pp (2014). [5] Zhang, Y., Liu, S., Tao, L., Yu, C., Shi, Y. and Xu, Y.: ChinAR: Facilitating Chinese Guqin Learning through Interactive Projected Augmentation, Proc. Chinese CHI 15, pp (2015). [6] Vol.52, No.2, pp (2011). [7] Vol.54, No.4, pp (2013). [8] Löchtefeld, M., Gehring, S., Jung, R. and Krüger, A.: guitar: supporting guitar learning through mobile projection, Proc. CHI EA 11, pp (2011). [9] Xiao, X., Tome, B. and Ishii, H.: Andante: Walking Figures on the Piano Keyboard to Visualize Musical Motion, Proc. NIME 14, pp (2014). [10] 2015 pp (2015). [11] Raymaekers, L., Vermeulen, J., Luyten, K. and Coninx, K.: Game of tones: Learning to Play Songs on a Piano Using Projected Instructions and Games, Proc. CHI EA 14, pp (2014). [12] Vol.11, No.3, pp (2012). [13] 2004-MUS-56 Vol.2004, No.84, pp (2004). [14] Aibiki 2014-HCI-157 Vol.2014, No.69, pp.1 6 (2014). [15] MUS-47 Vol.2002, No.100, pp (2002). A % [1] (2003). [2] (2002). [3] (2009). [4] Rogers, K., Röhlig, A., Weing, M., Gugenheimer, J., Könings, B., Klepsch, M., Schaub, F., Rukzio, E., Seufert, T. and Weber, M.: P.I.A.N.O.: Faster Piano c 2018 Information Processing Society of Japan 927

17 2017 A ACM c 2018 Information Processing Society of Japan 928

( ) [1] [4] ( ) 2. [5] [6] Piano Tutor[7] [1], [2], [8], [9] Radiobaton[10] Two Finger Piano[11] Coloring-in Piano[12] ism[13] MIDI MIDI 1 Fig. 1 Syst

( ) [1] [4] ( ) 2. [5] [6] Piano Tutor[7] [1], [2], [8], [9] Radiobaton[10] Two Finger Piano[11] Coloring-in Piano[12] ism[13] MIDI MIDI 1 Fig. 1 Syst 情報処理学会インタラクション 2015 IPSJ Interaction 2015 15INT014 2015/3/7 1,a) 1,b) 1,c) Design and Implementation of a Piano Learning Support System Considering Motivation Fukuya Yuto 1,a) Takegawa Yoshinari 1,b) Yanagi

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