On the Complex Network Structure of Musical Pieces: Analysis of Some Use Cases from Different Music Genres

This paper focuses on the modeling of musical melodies as networks. Notes of a melody can be treated as nodes of a network. Connections are created whenever notes are played in sequence. We analyze some main tracks coming from different music genres, with melodies played using different musical instruments. We find out that the considered networks are, in general, scale free networks and exhibit the small world property. We measure the main metrics and assess whether these networks can be considered as formed by sub-communities. Outcomes confirm that peculiar features of the tracks can be extracted from this analysis methodology. This approach can have an impact in several multimedia applications such as music didactics, multimedia entertainment, and digital music generation.Comment: accepted to Multimedia Tools and Applications, Springe

Composing first species counterpoint with a variable neighbourhood search algorithm

In this article, a variable neighbourhood search (VNS) algorithm is developed that can generate musical fragments consisting of a melody for the cantus firmus and the first species counterpoint. The objective function of the algorithm is based on a quantification of existing rules for counterpoint. The VNS algorithm developed in this article is a local search algorithm that starts from a randomly generated melody and improves it by changing one or two notes at a time. A thorough parametric analysis of the VNS reveals the significance of the algorithm's parameters on the quality of the composed fragment, as well as their optimal settings. A comparison of the VNS algorithm with a developed genetic algorithm shows that the VNS is more efficient. The VNS algorithm has been implemented in a user-friendly software environment for composition, called Optimuse. Optimuse allows a user to specify a number of characteristics such as length, key and mode. Based on this information, Optimuse 'composes' both cantus firmus and first species counterpoint. Alternatively, the user may specify a cantus firmus, and let Optimuse compose the accompanying first species counterpoint. © 2012 Taylor & Francis

Zipf's Law in Short-Time Timbral Codings of Speech, Music, and Environmental Sound Signals

Timbre is a key perceptual feature that allows discrimination between different sounds. Timbral sensations are highly dependent on the temporal evolution of the power spectrum of an audio signal. In order to quantitatively characterize such sensations, the shape of the power spectrum has to be encoded in a way that preserves certain physical and perceptual properties. Therefore, it is common practice to encode short-time power spectra using psychoacoustical frequency scales. In this paper, we study and characterize the statistical properties of such encodings, here called timbral code-words. In particular, we report on rank-frequency distributions of timbral code-words extracted from 740 hours of audio coming from disparate sources such as speech, music, and environmental sounds. Analogously to text corpora, we find a heavy-tailed Zipfian distribution with exponent close to one. Importantly, this distribution is found independently of different encoding decisions and regardless of the audio source. Further analysis on the intrinsic characteristics of most and least frequent code-words reveals that the most frequent code-words tend to have a more homogeneous structure. We also find that speech and music databases have specific, distinctive code-words while, in the case of the environmental sounds, this database-specific code-words are not present. Finally, we find that a Yule-Simon process with memory provides a reasonable quantitative approximation for our data, suggesting the existence of a common simple generative mechanism for all considered sound sources

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