2006
DOI: 10.1162/comj.2006.30.2.42
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Visualization in Audio-Based Music Information Retrieval

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Cited by 20 publications
(25 citation statements)
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“…Considering it is difficult to pre-attentively differentiate classical music from rock music with the MISUAL system, how can an individual expect to classify large music libraries when the differences between genres are so fine? [24] presents further research into static pragmatic visualizations for genre categorization. This paper covers multiple different techniques for music information retrieval visualization.…”
Section: Pragmatic Music Visualizationsmentioning
confidence: 99%
See 1 more Smart Citation
“…Considering it is difficult to pre-attentively differentiate classical music from rock music with the MISUAL system, how can an individual expect to classify large music libraries when the differences between genres are so fine? [24] presents further research into static pragmatic visualizations for genre categorization. This paper covers multiple different techniques for music information retrieval visualization.…”
Section: Pragmatic Music Visualizationsmentioning
confidence: 99%
“…This paper covers multiple different techniques for music information retrieval visualization. The commonalities between all the techniques in [24], including MISUAL's, are audio parameterization [24]. Audio is converted to data using Mel-Frequency Cepstral Coefficients, Fourier transforms and/or component analysis [24].…”
Section: Pragmatic Music Visualizationsmentioning
confidence: 99%
“…What matters in the end is the sound as such, not how it has been generated. Music Information Retrieval (MIR) offers methods that can help: Sounds can be classified and searched for by acoustic similarity, partially supported by visualization [3]. However, these methods are clearly limited in that they produce imprecise or wrong results in a substantial number of cases.…”
Section: Problem Settingmentioning
confidence: 99%
“…These data are represented through the spatial distance on the screen. This mapping from the wave form to geometric location employs MelFrequency Cepstral Coefficients and a self-organizing map, standard tools from Music Information Retrieval, which typically are applied to visualize collections of music files as landscapes of genres [3].…”
Section: Overview Of the Proposed Solutionmentioning
confidence: 99%
“…Given that such annotations are for retrieval purpose only, they will not contribute to the audio content itself. As for presenting audio content, there are lots efforts in terms of abstracting audio elements to visual cues [24] [25]. Among them, RadioActive [14] allows users to dictate voice messages.…”
Section: Related Workmentioning
confidence: 99%