2016
DOI: 10.1080/09298215.2015.1132737
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A Comparison of Approaches to Timbre Descriptors in Music Information Retrieval and Music Psychology

Abstract: A curious divide characterizes the usage of audio descriptors for timbre research in music information research (MIR) and music psychology. While MIR uses a multitude of audio descriptors for tasks such as automatic instrument classification, only a highly constrained set is used to describe the physical correlates of timbre perception in parts of music psychology. We argue that this gap is not coincidental and results from the differences in the two fields’ methodologies, their epistemic groundwork, and resea… Show more

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Cited by 52 publications
(38 citation statements)
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“…On the other hand, machine learning techniques that best recognize musical instruments, styles, etc. are not based on a few recurrent dimensions: they use and create whichever pieces statistical information fit a given classification task, relying on high-dimensional representations [94–97]. Another important result is that prior exposure to complex, abstract noise textures with little structure improves the performance at a subsequent repetition detection task [98].…”
Section: Discussionmentioning
confidence: 99%
“…On the other hand, machine learning techniques that best recognize musical instruments, styles, etc. are not based on a few recurrent dimensions: they use and create whichever pieces statistical information fit a given classification task, relying on high-dimensional representations [94–97]. Another important result is that prior exposure to complex, abstract noise textures with little structure improves the performance at a subsequent repetition detection task [98].…”
Section: Discussionmentioning
confidence: 99%
“…Yet, questions regarding the most perceptually relevant acoustical descriptors of the spectral envelope prevail (cf. Siedenburg et al, 2016;Almeida et al, 2017).…”
Section: Introductionmentioning
confidence: 99%
“…Consistent with this, a recent paper reviews the disparities in outlook and purpose (even towards timbre) between music psychology and other fields, and suggests approaches to bring them together productively [34]. The present study begins to address such disparities by investigating predictors amongst acoustic factors, particularly spectral features, which might model and potentially explain listeners' perceptions.…”
Section: Introductionmentioning
confidence: 65%