2019
DOI: 10.1109/access.2019.2944083
|View full text |Cite
|
Sign up to set email alerts
|

Music Visualization Based on Spherical Projection With Adjustable Metrics

Abstract: Development of techniques for music visualization is important and still open problem in analysis and creation of the quantitative profiles of single or multiple compositions, which could be used as required constraints in music generation or music classification processes. When generating creative data with no objective function, it is hard to select or to find appropriate measurable features. This paper proposes a method to normalize data in MIDI files by 12 dimensional vector descriptors extracted from tona… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1

Citation Types

0
1
0

Year Published

2022
2022
2024
2024

Publication Types

Select...
3
2

Relationship

0
5

Authors

Journals

citations
Cited by 7 publications
(1 citation statement)
references
References 20 publications
0
1
0
Order By: Relevance
“…Integrating the analyst into the analysis process to support knowledge generation and verification [SSS*14] is necessary since exclusively computational approaches [Urb17] cannot model human intuition about semantic meaning. In the visualization domain, graph‐based [HMM00], matrix‐based [KS10] and projection‐based [LS19] techniques have been proposed to facilitate the visual analysis at different levels of abstraction. Such data‐driven, abstract visualizations are meant to assist the music analysis process but lack a suitable connection to the CMN.…”
Section: Introductionmentioning
confidence: 99%
“…Integrating the analyst into the analysis process to support knowledge generation and verification [SSS*14] is necessary since exclusively computational approaches [Urb17] cannot model human intuition about semantic meaning. In the visualization domain, graph‐based [HMM00], matrix‐based [KS10] and projection‐based [LS19] techniques have been proposed to facilitate the visual analysis at different levels of abstraction. Such data‐driven, abstract visualizations are meant to assist the music analysis process but lack a suitable connection to the CMN.…”
Section: Introductionmentioning
confidence: 99%