2005
DOI: 10.1121/1.4785911
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Application of musical timbre discrimination features to active sonar classification

Abstract: In musical acoustics significant effort has been devoted to uncovering the physical basis of timbre perception. Most investigations into timbre rely on multidimensional scaling (MDS), in which different musical sounds are arranged as points in multidimensional space. The Euclidean distance between points corresponds to the perceptual distance between sounds and the multidimensional axes are linked to measurable properties of the sounds. MDS has identified numerous temporal and spectral features believed to be … Show more

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Cited by 3 publications
(4 citation statements)
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“…mean, standard deviation, skewness, kurtosis). Others were perceptually-motivated features from previous perceptual studies ( [4], [7], [9]). These features include time-frequency features such as subband correlation, subband rise time, and spectral flux, as well as other classes of features.…”
Section: Resultsmentioning
confidence: 99%
“…mean, standard deviation, skewness, kurtosis). Others were perceptually-motivated features from previous perceptual studies ( [4], [7], [9]). These features include time-frequency features such as subband correlation, subband rise time, and spectral flux, as well as other classes of features.…”
Section: Resultsmentioning
confidence: 99%
“…38 Therefore, this feature becomes an important descriptor for sets of signals with different numbers of overtones. The humpback units consistently had larger sub-band correlation values than the bowhead end notes because they have more overtones.…”
Section: Important Perceptual Featuresmentioning
confidence: 99%
“…Since the perceptual loudness spectrum is essentially a psychoacoustic power spectrum, the peak loudness value (in sones/ERB) is analogous to the peak power of a signal's spectrum and the peak loudness frequency (in ERB) is analogous to the frequency at which the peak power occurred. 38 Note that because the perceptual loudness spectrum of each vocalization was scaled for complete audibility across the full bandwidth of interest (as described in Sec. III A) the peak loudness value was not just a measure of the relative received levels of the vocalizations, but instead provided an indication of how energy was distributed within each perceptual loudness spectrum.…”
Section: Important Perceptual Featuresmentioning
confidence: 99%
“…mean, standard deviation, skewness, kurtosis). Others were perceptually-motivated features found from previous perceptual studies [1,14,49]. These features include time-frequency features such as subband correlation, subband rise time, and spectral flux, as well as other classes of features.…”
Section: Standard Mds Analysismentioning
confidence: 99%