Dear all, I'm pleased to announce v1. 8 of IDyOM (Information Dynamics of Music). Documentation and downloads are available at: https: //mtpearce. github. io/idyom/ This release contains updates to harmony modelling alongside general bug fixes.
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Dear all,
I'm pleased to announce v1.8 of IDyOM (Information Dynamics of
Music). Documentation and downloads are available at:
This release contains updates to harmony modelling alongside general
bug fixes. There is also improved documentation for modelling
harmony and similarity as well as tools for music generation and key
finding. See the README for full details of new features in this
release.
IDyOM is a computational framework for constructing
multiple-viewpoint, variable-order Markov models for predictive
modelling of probabilistic structure in symbolic, sequential
auditory domains such as music. IDyOM acquires information about a
domain through statistical learning and generates conditional
probability distributions representing the estimated likelihood of
each event in a sequence, plus associated information-theoretic
measures, given the preceding context and prior short- and long-term
training of the model. IDyOM has been used to simulate musical
expectations, perceptual similarity, auditory memory, complexity
perception and experience of pleasure.
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