An approach to melodic segmentation and classification based on filtering with the Haar wavelet

We present a novel method of classification and segmentation of melodies in symbolic representation. The method is based on filtering pitch as a signal over time with the Haar-wavelet, and we evaluate it on two tasks. The filtered signal corresponds to a single-scale signal ws from the continuous Haar wavelet transform. The melodies are first segmented using local maxima or zero-crossings of ws. The segments of ws are then classified using the k–nearest neighbour algorithm with Euclidian and city-block distances. The method proves more effective than using unfiltered pitch signals and Gestalt-based segmentation when used to recognize the parent works of segments from Bach’s Two-Part Inventions (BWV 772–786). When used to classify 360 Dutch folk tunes into 26 tune families, the performance of the method is comparable to the use of pitch signals, but not as good as that of string-matching methods based on multiple features

Variational Hilbert space truncation approach to quantum Heisenberg antiferromagnets on frustrated clusters

We study the spin-$\frac{1}{2}$ Heisenberg antiferromagnet on a series of finite-size clusters with features inspired by the fullerenes. Frustration due to the presence of pentagonal rings makes such structures challenging in the context of quantum Monte-Carlo methods. We use an exact diagonalization approach combined with a truncation method in which only the most important basis states of the Hilbert space are retained. We describe an efficient variational method for finding an optimal truncation of a given size which minimizes the error in the ground state energy. Ground state energies and spin-spin correlations are obtained for clusters with up to thirty-two sites without the need to restrict the symmetry of the structures. The results are compared to full-space calculations and to unfrustrated structures based on the honeycomb lattice.Comment: 22 pages and 12 Postscript figure

Information dynamics: patterns of expectation and surprise in the perception of music

This is a postprint of an article submitted for consideration in Connection Science © 2009 [copyright Taylor & Francis]; Connection Science is available online at:http://www.tandfonline.com/openurl?genre=article&issn=0954-0091&volume=21&issue=2-3&spage=8

Generation of folk song melodies using Bayes transforms

The paper introduces the `Bayes transform', a mathematical procedure for putting data into a hierarchical representation. Applicable to any type of data, the procedure yields interesting results when applied to sequences. In this case, the representation obtained implicitly models the repetition hierarchy of the source. There are then natural applications to music. Derivation of Bayes transforms can be the means of determining the repetition hierarchy of note sequences (melodies) in an empirical and domain-general way. The paper investigates application of this approach to Folk Song, examining the results that can be obtained by treating such transforms as generative models

Pleasure, arousal, dominance, and judgments about music in everyday life

The aim of the present research was to consider what particular features are significant predictors of whether music is present in a given situation, as well as what factors influence a person’s judgments about the music. Applying Mehrabian and Russell’s (1974) Pleasure-Arousal-Dominance model to everyday experiences of music, 569 people reported on their activity for the previous day via the Day Reconstruction Method (Kahneman, Krueger, Schkade, Schwarz, & Stone, 2004). Data concerning each event included the activity and location, and characterization of the experience using the Pleasure–Arousal–Dominance measure. Moreover, for those events where music was present, participants also indicated how they heard the music and made four judgments about the music. Results indicated that the location, activity, and the person’s perception of dominance were significant predictors of the presence of music during everyday activities and that person’s judgments about the music. Contrary to prior research that has considered predominantly situational pleasure and arousal variables, the present results demonstrate that dominance is arguably the important variable in contextualized music listening

Cognitive and affective judgements of syncopated musical themes

This study investigated cognitive and emotional effects of syncopation, a feature of musical rhythm that produces expectancy violations in the listener by emphasising weak temporal locations and de-emphasising strong locations in metric structure. Stimuli consisting of pairs of unsyncopated and syncopated musical phrases were rated by 35 musicians for perceived complexity, enjoyment, happiness, arousal, and tension. Overall, syncopated patterns were more enjoyed, and rated as happier, than unsyncopated patterns, while differences in perceived tension were unreliable. Complexity and arousal ratings were asymmetric by serial order, increasing when patterns moved from unsyncopated to syncopated, but not significantly changing when order was reversed. These results suggest that syncopation influences emotional valence (positively), and that while syncopated rhythms are objectively more complex than unsyncopated rhythms, this difference is more salient when complexity increases than when it decreases. It is proposed that composers and improvisers may exploit this asymmetry in perceived complexity by favoring formal structures that progress from rhythmically simple to complex, as can be observed in the initial sections of musical forms such as theme and variations

A Standardised Procedure for Evaluating Creative Systems: Computational Creativity Evaluation Based on What it is to be Creative

Computational creativity is a flourishing research area, with a variety of creative systems being produced and developed. Creativity evaluation has not kept pace with system development with an evident lack of systematic evaluation of the creativity of these systems in the literature. This is partially due to difficulties in defining what it means for a computer to be creative; indeed, there is no consensus on this for human creativity, let alone its computational equivalent. This paper proposes a Standardised Procedure for Evaluating Creative Systems (SPECS). SPECS is a three-step process: stating what it means for a particular computational system to be creative, deriving and performing tests based on these statements. To assist this process, the paper offers a collection of key components of creativity, identified empirically from discussions of human and computational creativity. Using this approach, the SPECS methodology is demonstrated through a comparative case study evaluating computational creativity systems that improvise music

Active Learning for Auditory Hierarchy

Much audio content today is rendered as a static stereo mix: fundamentally a fixed single entity. Object-based audio envisages the delivery of sound content using a collection of individual sound ‘objects’ controlled by accompanying metadata. This offers potential for audio to be delivered in a dynamic manner providing enhanced audio for consumers. One example of such treatment is the concept of applying varying levels of data compression to sound objects thereby reducing the volume of data to be transmitted in limited bandwidth situations. This application motivates the ability to accurately classify objects in terms of their ‘hierarchy’. That is, whether or not an object is a foreground sound, which should be reproduced at full quality if possible, or a background sound, which can be heavily compressed without causing a deterioration in the listening experience. Lack of suitably labelled data is an acknowledged problem in the domain. Active Learning is a method that can greatly reduce the manual effort required to label a large corpus by identifying the most effective instances to train a model to high accuracy levels. This paper compares a number of Active Learning methods to investigate which is most effective in the context of a hierarchical labelling task on an audio dataset. Results show that the number of manual labels required can be reduced to 1.7% of the total dataset while still retaining high prediction accuracy

Nucleation of a sodium droplet on C60

We investigate theoretically the progressive coating of C60 by several sodium atoms. Density functional calculations using a nonlocal functional are performed for NaC60 and Na2C60 in various configurations. These data are used to construct an empirical atomistic model in order to treat larger sizes in a statistical and dynamical context. Fluctuating charges are incorporated to account for charge transfer between sodium and carbon atoms. By performing systematic global optimization in the size range 1<=n<=30, we find that Na_nC60 is homogeneously coated at small sizes, and that a growing droplet is formed above n=>8. The separate effects of single ionization and thermalization are also considered, as well as the changes due to a strong external electric field. The present results are discussed in the light of various experimental data.Comment: 17 pages, 10 figure