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\title{Cognitive Information Processing Workshop Paper Outline}


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\abstract{What is our core hypthesis? \emph{People take in information when perceiving music.  With it they continually build predictive models of what is going to happen.  An information theoretic approach to music cognition is thus a fruitful avenue of research.}}


\section{Intro}
\subsection{Information Theory and prediction}
Bayesian probabillity and modeling the building of predictions
\subsection{Link to music}
Music as a temporal pattern.  Meyer, Narmour. Music unfolding in time.  How listeners see different kinds of predictability in musical patters..
\section{Information Dynamics Approach}

\subsection{Re-iterate core hypothesis}

\subsection{models/parameters/observations}
The grouping of elements into past, present and future..s
\subsection{Information measures}
Predictive information rate as a measure of structure 
Cruchfield papers, anatomy of abit
\subsection{Case of this approach being good at modelling music cognition}
Inverted U
\section{Applications}
\subsection{Information Dynamics as Design Tool }
\subsubsection{The Melody Triangle}
	What it is
	
	As composition assistant
	
	generation of non-sonic content \emph{maybe?}

\subsubsection{Boredom detector?}

\subsubsection{Musical Preference and Information Dynamics}
   Any results from this study
\subsection{In Analysis}
	refer to the work with the analysis of minimalist pieces
	
	Content analysis - Sound Categorisation.  Using Information Dynamics it is possible to segment music.  From there we can then use this to search large data sets. Determine musical structure for the purpose of playlist navigation and search. (Peter)

\subsection{Beat Tracking}
  Bayesian belief can be used to predict when things happen (as oppose to just what happens).  Information Dynamics of?
  

\section{Conclusion}

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