Comparing Probabilistic Models for Melodic Sequences

Modelling the real world complexity of music is a challenge for machine learning. We address the task of modeling melodic sequences from the same music genre. We perform a comparative analysis of two probabilistic models; a Dirichlet Variable Length Markov Model (Dirichlet-VMM) and a Time Convolutional Restricted Boltzmann Machine (TC-RBM). We show that the TC-RBM learns descriptive music features, such as underlying chords and typical melody transitions and dynamics. We assess the models for future prediction and compare their performance to a VMM, which is the current state of the art in melody generation. We show that both models perform significantly better than the VMM, with the Dirichlet-VMM marginally outperforming the TC-RBM. Finally, we evaluate the short order statistics of the models, using the Kullback-Leibler divergence between test sequences and model samples, and show that our proposed methods match the statistics of the music genre significantly better than the VMM.Comment: in Proceedings of the ECML-PKDD 2011. Lecture Notes in Computer Science, vol. 6913, pp. 289-304. Springer (2011

A response to Tom Barney

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/68308/2/10.1177_096394709500400104.pd

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

The Rhythm Span Task: Comparing Memory Capacity for Musical Rhythms in Musicians and Non-Musicians

The study introduces a rhythm memory task and compares performance of musicians and non-musicians. The rhythm span task with increasing and decreasing sequence length according to the participants’ performance, measures the individual memory capacity for musical rhythms. Results show that musicians perform significantly better on the rhythm span task indicating that memory capacity for rhythms is superior after many years of formal musical training. Additionally performance correlates positively with an established pitch span task (Williamson & Stewart, 2010) as well as the five dimensions of the Gold-MSI self-report questionnaire (Müllensiefen et al., 2014) evaluating musical sophistication

Shall We (Math and) Dance?

Can we use mathematics, and in particular the abstract branch of category theory, to describe some basics of dance, and to highlight structural similarities between music and dance? We first summarize recent studies between mathematics and dance, and between music and categories. Then, we extend this formalism and diagrammatic thinking style to dance.Comment: preprin

Spring School on Language, Music, and Cognition: Organizing Events in Time

The interdisciplinary spring school “Language, music, and cognition: Organizing events in time” was held from February 26 to March 2, 2018 at the Institute of Musicology of the University of Cologne. Language, speech, and music as events in time were explored from different perspectives including evolutionary biology, social cognition, developmental psychology, cognitive neuroscience of speech, language, and communication, as well as computational and biological approaches to language and music. There were 10 lectures, 4 workshops, and 1 student poster session. Overall, the spring school investigated language and music as neurocognitive systems and focused on a mechanistic approach exploring the neural substrates underlying musical, linguistic, social, and emotional processes and behaviors. In particular, researchers approached questions concerning cognitive processes, computational procedures, and neural mechanisms underlying the temporal organization of language and music, mainly from two perspectives: one was concerned with syntax or structural representations of language and music as neurocognitive systems (i.e., an intrapersonal perspective), while the other emphasized social interaction and emotions in their communicative function (i.e., an interpersonal perspective). The spring school not only acted as a platform for knowledge transfer and exchange but also generated a number of important research questions as challenges for future investigations

A Memetic Analysis of a Phrase by Beethoven: Calvinian Perspectives on Similarity and Lexicon-Abstraction

This article discusses some general issues arising from the study of similarity in music, both human-conducted and computer-aided, and then progresses to a consideration of similarity relationships between patterns in a phrase by Beethoven, from the first movement of the Piano Sonata in A flat major op. 110 (1821), and various potential memetic precursors. This analysis is followed by a consideration of how the kinds of similarity identified in the Beethoven phrase might be understood in psychological/conceptual and then neurobiological terms, the latter by means of William Calvin’s Hexagonal Cloning Theory. This theory offers a mechanism for the operation of David Cope’s concept of the lexicon, conceived here as a museme allele-class. I conclude by attempting to correlate and map the various spaces within which memetic replication occurs

Synchronization to a bouncing ball with a realistic motion trajectory

Daily music experience involves synchronizing movements in time with a perceived periodic beat. It has been established for over a century that beat synchronization is less stable for the visual than for the auditory modality. This auditory advantage of beat synchronization gives rise to the hypotheses that the neural and evolutionary mechanisms underlying beat synchronization are modality-specific. Here, however, we found that synchronization to a periodically bouncing ball with a realistic motion trajectory was not less stable than synchronization to an auditory metronome. This finding challenges the auditory advantage of beat synchronization, and has important implications for the understanding of the biological substrates of beat synchronization