PRISM is a probabilistic-logical programming language based on Prolog. We present a PRISM-implementation of a general model for polyphonic music, based on Hidden Markov Models. Its probability parameters are automatically learned by running the built-in EM-algorithm of PRISM on training examples. We show how the model can be used as a classifier for music that guesses the composer of unknown fragments of music. Then we use it to automatically compose new music.status: publishe
Probabilistic Logic Programming extends Logic Programming by enabling the representation of uncertai...
This dissertation describes a chorale harmonisation system which uses Hidden Markov Models. We use a...
The design of algorithms modelled on the abstraction of compositional formalisms has been practised...
International audienceAnalyzing and formalizing the intricate mechanisms of music is a very challeng...
Hidden Markov Models have been used frequently in the audio domain to identify underlying musical st...
A technique for harmonic analysis is presented that partitions a piece of music into contiguous regi...
We describe how we used a data set of chorale harmonisations composed by Johann Sebastian Bach to tr...
We present a new system for automatic music generation, in which music is modeled using very high le...
The combination of logic programming and probability has proven useful for modeling domains with com...
Probabilistic programming is an emerging subfield of AI that extends traditional programming languag...
Recently much work in Machine Learning has concentrated on representation languages able to combine...
Natural systems are the source of inspiration for the human tendency to pursue creative endeavors. ...
Recently much work in Machine Learning has concentrated on using expressive representation languages...
PRISM was born in 1997 as a symbolic statistical modeling language to facilitate modeling complex sy...
Recently much work in Machine Learning has concentrated on using expressive representation languages...
Probabilistic Logic Programming extends Logic Programming by enabling the representation of uncertai...
This dissertation describes a chorale harmonisation system which uses Hidden Markov Models. We use a...
The design of algorithms modelled on the abstraction of compositional formalisms has been practised...
International audienceAnalyzing and formalizing the intricate mechanisms of music is a very challeng...
Hidden Markov Models have been used frequently in the audio domain to identify underlying musical st...
A technique for harmonic analysis is presented that partitions a piece of music into contiguous regi...
We describe how we used a data set of chorale harmonisations composed by Johann Sebastian Bach to tr...
We present a new system for automatic music generation, in which music is modeled using very high le...
The combination of logic programming and probability has proven useful for modeling domains with com...
Probabilistic programming is an emerging subfield of AI that extends traditional programming languag...
Recently much work in Machine Learning has concentrated on representation languages able to combine...
Natural systems are the source of inspiration for the human tendency to pursue creative endeavors. ...
Recently much work in Machine Learning has concentrated on using expressive representation languages...
PRISM was born in 1997 as a symbolic statistical modeling language to facilitate modeling complex sy...
Recently much work in Machine Learning has concentrated on using expressive representation languages...
Probabilistic Logic Programming extends Logic Programming by enabling the representation of uncertai...
This dissertation describes a chorale harmonisation system which uses Hidden Markov Models. We use a...
The design of algorithms modelled on the abstraction of compositional formalisms has been practised...