Music learning through visualization

Hiraga, Rumi; Watanabe, Fumiko; Fujishiro, Issei

doi:10.1109/wdm.2002.1176199

Cited by 13 publications

(24 citation statements)

References 10 publications

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“…Audio features extracted from music performances like pitch, loudness, tempo and timing are the basis for related visualizations. Some works use a combination of audio features and score data [HWF02, Isa03]. For the works considered in this section, score data play a secondary role.…”

Section: Classificationmentioning

confidence: 99%

A Survey on Visualizations for Musical Data

Khulusi

Kusnick

Meinecke

et al. 2020

Computer Graphics Forum

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Digital methods are increasingly applied to store, structure and analyse vast amounts of musical data. In this context, visualization plays a crucial role, as it assists musicologists and non‐expert users in data analysis and in gaining new knowledge. This survey focuses on this unique link between musicology and visualization. We classify 129 related works according to the visualized data types, and we analyse which visualization techniques were applied for certain research inquiries and to fulfill specific tasks. Next to scientific references, we take commercial music software and public websites into account, that contribute novel concepts of visualizing musicological data. We encounter different aspects of uncertainty as major problems when dealing with musicological data and show how occurring inconsistencies are processed and visually communicated. Drawing from our overview in the field, we identify open challenges for research on the interface of musicology and visualization to be tackled in the future.

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Section: Classificationmentioning

confidence: 99%

A Survey on Visualizations for Musical Data

Khulusi

Kusnick

Meinecke

et al. 2020

Computer Graphics Forum

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show abstract

“…Hiraga showed the change of performance expression beyond the MIDI parameter level on a series of Chernoff faces[3,5].…”

mentioning

confidence: 99%

Performance visualization

Hiraga

Mizaki

Fujishiro

2002

Proceedings of the Tenth ACM International Conference on Multimedia

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This paper describes performance visualization with its purposes, significance, and our prototype system. Performance visualization provides us with a new user interface for music systems, a non-subjective explanation and judgment for musical expression, and a visual aid to understand, analyze, and compare performances and their musical structures. It will also introduce a more challenging research on designing a musical data mining interface not by tags nor by contents but by the mood. Other challenges include finding qualitative characteristics of music with analysis methods for information visualization and synesthesia between visualized and sonified information. We will describe which information should be shown on the visualized figures for expressive performance. Then we will show our prototype system to visualize expressive performance consisting of several instruments.

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“…[28], para permitir a exploração de uma composição musical ao mesmo tempo em que a estrutura geral dos dados ainda pode ser observada, compreendendo assim uma visão focus+context [1]. Este modelo foi utilizado em conjunto com uma aplicação de rostos de Chernoff [30] para formar um sistema destinado ao aprendizado e treinamento de músicos [31].…”

Section: Figuraunclassified

Visualização computacional de música com suporte à discriminação de elementos de teoria musical

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Music learning through visualization

Cited by 13 publications

References 10 publications

A Survey on Visualizations for Musical Data

A Survey on Visualizations for Musical Data

Performance visualization

Visualização computacional de música com suporte à discriminação de elementos de teoria musical

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