1. Transactional Leadership Style, Job Satisfaction and Organizational Commitment to Employee Performance on Collection Section of Bank X Surabaya
- Author
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Karya, Denis Fidita, Mardhotillah, Rachma Rizqina, and Sahrin, Laila Alfi
- Subjects
Lightness ,ComputingMilieux_THECOMPUTINGPROFESSION ,Music psychology ,business.industry ,Computer science ,Speech recognition ,Matrix (music) ,Pattern recognition ,Music visualization ,Visualization ,Duration (music) ,Artificial intelligence ,Mel-frequency cepstrum ,business ,Tonality - Abstract
This paper proposes a method to identify and visualize repetitive structures in a pairwise representation of music to support people to imagine their affinity for music and the lightness of music intuitively, or in other words without listening to it. Repetitive structures in this paper are fragments that a music piece contains multiple times, and all these fragments may be slightly different but are perceived as very similar. For example, a tune might have little difference in tonality and could be performed by different kinds of musical instruments. We propose an algorithm to identify repetitive structures in a tune by using a self-similarity matrix. Identified structures are visualized on two kinds of images. One is a colored cylinder of varying diameter where colors represent repetitions and the diameter represents volume changes; the other is repetitions lines image, where different pairs of repetitions are shown on the Y-axis and the duration of each repeated pair is shown on the X-axis with a color. We selected eight tunes based on music psychology to evaluate the performance of the identification and visualization technique. Finally, we found that the amount of repetitions is related to the affinity for music, but not to the lightness of music. Volumes in both high-affinity music and high-lightness music change drastically.
- Published
- 2021
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