On the spectral analysis of melody

Nettheim, Nigel

doi:10.1080/09298219208570604

Cited by 28 publications

(41 citation statements)

References 6 publications

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“…Perhaps it is possible that from further statistical studies, new classification methods of authors pieces and kinds of music can arise, even thought no distinction between different kind of music seems to emerge from spectral analysis [4,5,6,7].…”

Section: Resultsmentioning

confidence: 99%

“…Voss and Clarke [4,5] found that the spectral density S(f ) of V 2 (t) exhibits a 1/f power spectra in the low frequency range (< 10Hz) in many musical selections and in English speech. Recent measurements [6,7] give S(f ) ≃ f −ν in the low frequency range with ν = 1, but no correlation between the analyzed music and the ν value seems to emerge.…”

Section: Discussionmentioning

confidence: 99%

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Different amplitude and time distribution of the sound of light and classical music

Diodati

Piazza

2000

Eur. Phys. J. B

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Abstract. Several pieces of different musical kinds were studied measuring N (A), the output amplitude of a peak detector driven by the electric signal arriving to the loudspeaker. Fixed a suitable thresholdĀ, we considered N (A), the number of times that A(t) >Ā, each of them we named event and N (t), the distribution of times t between two consecutive events. Some N (A) and N (t) distributions are displayed in the reported logarithmic plots, showing that jazz, pop, rock and other popular rhythms have noisedistribution, while classical pieces of music are characterized by more complex statistics. We pointed out the extraordinary case of the aria "La calunniaè un venticello", where the words describe an avalanche or seismic process, calumny, and the rossinian music shows N (A) and N (t) distribution typical of earthquakes. PACS

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Section: Resultsmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Different amplitude and time distribution of the sound of light and classical music

Diodati

Piazza

2000

Eur. Phys. J. B

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“…Some attempt to understand this meaning and its effect on the listener by dissecting the aesthetic experience in terms of separable, discrete sounds. Others attempt to find it in terms of grouping stimuli into patterns and studying their hierarchical organization [4], [10], [11], [15], [16]. Meyer [13, p. 342] suggests that emotional states in music (sad, angry, happy, etc.)…”

Section: Introductionmentioning

confidence: 99%

Evolutionary Music and the Zipf-Mandelbrot Law: Developing Fitness Functions for Pleasant Music

Manaris

Vaughan

Wagner

et al. 2003

Lecture Notes in Computer Science

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Abstract.A study on a 220-piece corpus (baroque, classical, romantic, 12-tone, jazz, rock, DNA strings, and random music) reveals that aesthetically pleasing music may be describable under the Zipf-Mandelbrot law. Various Zipf-based metrics have been developed and evaluated. Some focus on musictheoretic attributes such as pitch, pitch and duration, melodic intervals, and harmonic intervals. Others focus on higher-order attributes and fractal aspects of musical balance. Zipf distributions across certain dimensions appear to be a necessary, but not sufficient condition for pleasant music. Statistical analyses suggest that combinations of Zipf-based metrics might be used to identify genre and/or composer. This is supported by a preliminary experiment with a neural network classifier. We describe an evolutionary music framework under development, which utilizes Zipf-based metrics as fitness functions.

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“…For this purpose, Voss and Clarke (1978) suggested that white noise is too random, brown is too correlated, but pink is just right; they also presented empirical evidence that pink noise is prevalent in music. Nettheim (1992), however, subsequently demonstrated that, under a more precise analytical method, the pitch distributions in common-practice music (for lags of up to four bars) tend more towards 1/f 2 than 1/f . Recent analyses of John Coltrane's solos also show spectra closer to 1/f 2 than to 1/f (Charyton 2015).…”

Section: Noisementioning

confidence: 99%

Linking Sonic Aesthetics with Mathematical Theories

Milne

2018

Oxford Handbooks Online

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Pure mathematics provides principles, procedures, and ways of thinking that can be fruitful starting points for music composition, performance, and algorithmic generation. In this chapter, a number of mathematical methods are suggested as useful ways to define and transform underlying musical structures such as meters and scales, and to realize these structures as finished pieces of music. The mathematical methods include the discrete Fourier transform, geometry, algebraic word theory, and tiling, and how these relate to musical features such as periodicity (or lack of periodicity), well-formedness, microtonality, canons, rhythmic hierarchies, and polyrhythms. The chapter closes with a detailed examination of a musical piece derived from the described processes.

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On the spectral analysis of melody

Cited by 28 publications

References 6 publications

Different amplitude and time distribution of the sound of light and classical music

Different amplitude and time distribution of the sound of light and classical music

Evolutionary Music and the Zipf-Mandelbrot Law: Developing Fitness Functions for Pleasant Music

Linking Sonic Aesthetics with Mathematical Theories

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