The construction and evaluation of statistical models of melodic structure in music perception and composition. Pearce, M. T. Ph.D. Thesis, City University of London, 2005.
The construction and evaluation of statistical models of melodic structure in music perception and composition [link]Paper  abstract   bibtex   
The prevalent approach to developing cognitive models of music perception and composition is to construct systems of symbolic rules and constraints on the basis of extensive music-theoretic and music-analytic knowledge. The thesis proposed in this dissertation is that statistical models which acquire knowledge through the induction of regularities in corpora of existing music can, if examined with appropriate methodologies, provide significant insights into the cognitive processing involved in music perception and composition. This claim is examined in three stages. First, a number of statistical modelling techniques drawn from the fields of data compression, statistical language modelling and machine learning are subjected to empirical evaluation in the context of sequential prediction of pitch structure in unseen melodies. This investigation results in a collection of modelling strategies which together yield significant performance improvements over existing methods. In the second stage, these statistical systems are used to examine observed patterns of expectation collected in previous psychological research on melody perception. In contrast to previous accounts of this data, the results demonstrate that these patterns of expectation can be accounted for in terms of the induction of statistical regularities acquired through exposure to music. In the final stage of the present research, the statistical systems developed in the first stage are used to examine the intrinsic computational demands of the task of composing a stylistically successful melody The results suggest that the systems lack the degree of expressive power needed to consistently meet the demands of the task. In contrast to previous research, however, the methodological framework developed for the evaluation of computational models of composition enables a detailed empirical examination and comparison of such models which facilitates the identification and resolution of their weaknesses.
@PhDThesis{        pearce2005-construction,
    author       = {Pearce, Marcus Thomas},
    year         = {2005},
    title        = {The construction and evaluation of statistical models of
                   melodic structure in music perception and composition},
    abstract     = {The prevalent approach to developing cognitive models of
                   music perception and composition is to construct systems
                   of symbolic rules and constraints on the basis of
                   extensive music-theoretic and music-analytic knowledge.
                   The thesis proposed in this dissertation is that
                   statistical models which acquire knowledge through the
                   induction of regularities in corpora of existing music
                   can, if examined with appropriate methodologies, provide
                   significant insights into the cognitive processing
                   involved in music perception and composition. This claim
                   is examined in three stages. First, a number of
                   statistical modelling techniques drawn from the fields of
                   data compression, statistical language modelling and
                   machine learning are subjected to empirical evaluation in
                   the context of sequential prediction of pitch structure in
                   unseen melodies. This investigation results in a
                   collection of modelling strategies which together yield
                   significant performance improvements over existing
                   methods. In the second stage, these statistical systems
                   are used to examine observed patterns of expectation
                   collected in previous psychological research on melody
                   perception. In contrast to previous accounts of this data,
                   the results demonstrate that these patterns of expectation
                   can be accounted for in terms of the induction of
                   statistical regularities acquired through exposure to
                   music. In the final stage of the present research, the
                   statistical systems developed in the first stage are used
                   to examine the intrinsic computational demands of the task
                   of composing a stylistically successful melody The results
                   suggest that the systems lack the degree of expressive
                   power needed to consistently meet the demands of the task.
                   In contrast to previous research, however, the
                   methodological framework developed for the evaluation of
                   computational models of composition enables a detailed
                   empirical examination and comparison of such models which
                   facilitates the identification and resolution of their
                   weaknesses.},
    keywords     = {music analysis with computers},
    mendeley-tags= {music analysis with computers},
    school       = {City University of London},
    type         = {Ph.D. Dissertation},
    url          = {http://openaccess.city.ac.uk/id/eprint/8459/}
}
Downloads: 0
About
Documentation
Keywords
Search
Users
Terms and Conditions of Use
Privacy Policy
Sitemap
© BibBase.org 2021