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1 \newcommand{\postscriptref}[1] {(\emph{see} \textbf{#1})}
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2 \providecommand{\url}[1] {\texttt{#1}}
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3 \begin{thebibliography}{SJAN99}
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4
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5 \bibitem[Ber71]{Berlyne71}
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6 D.~E. Berlyne.
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7 \newblock {\em Aesthetics and Psychobiology}.
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8 \newblock Appleton Century Crofts, New York, 1971.
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9
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10 \bibitem[Coh62]{Cohen1962}
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11 J.~E. Cohen.
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12 \newblock Information theory and music.
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13 \newblock {\em Behavioral Science}, 7(2):137--163, 1962.
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14
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15 \bibitem[Cox46]{Cox1946}
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16 Richard~T. Cox.
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17 \newblock Probability, frequency and reasonable expectation.
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18 \newblock {\em American Journal of Physics}, 14:1--13, 1946.
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19
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20 \bibitem[CW95]{ConklinWitten95}
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21 Darrell Conklin and Ian~H. Witten.
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22 \newblock Multiple viewpoint systems for music prediction.
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23 \newblock {\em Journal of New Music Research}, 24(1):51--73, 1995.
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24
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25 \bibitem[dF75]{deFinetti}
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26 Bruno de~Finetti.
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27 \newblock {\em Theory of Probability}.
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28 \newblock John Wiley and Sons, New York, 1975.
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29
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30 \bibitem[ETK02]{EerolaToiviainenKrumhansl2002}
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31 T.~Eerola, P.~Toiviainen, and C.~L. Krumhansl.
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32 \newblock Real-time prediction of melodies: Continous predictability judgments
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33 and dynamic models.
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34 \newblock In C.~Stevens, D.~Burnham, G.~McPherson, E.~Schubert, and J.~Renwick,
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35 editors, {\em Proceedings of the 7th International Conference on Music
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37 Productions.
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38
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39 \bibitem[Han86]{Hanslick1854}
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40 Eduard Hanslick.
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41 \newblock {\em On the musically beautiful: A contribution towards the revision
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42 of the aesthetics of music}.
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43 \newblock Hackett, Indianapolis, IN, 1854/1986.
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44
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45 \bibitem[HO95]{HausslerOpper1995}
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46 David Haussler and Manfred Opper.
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47 \newblock General bounds on the mutual information between a parameter and n
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48 conditionally independent observations.
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49 \newblock In {\em Proceedings of the Seventh Annual ACM Workshop on
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50 Computational learning theory (COLT '95)}, pages 402--411, New York, NY, USA,
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51 1995. ACM.
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52
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53 \bibitem[IB05]{IttiBaldi2005}
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54 Laurent Itti and Pierre Baldi.
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55 \newblock Bayesian surprise attracts human attention.
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56 \newblock In {\em Advances Neural in Information Processing Systems (NIPS
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57 2005)}, volume~19, pages 547--554, Cambridge, MA, 2005. MIT Press.
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58
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59 \bibitem[Jay88]{Jaynes27}
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60 Edwin~T. Jaynes.
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61 \newblock How does the brain do plausible reasoning?
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62 \newblock In G.~J. Erickson and C.~R. Smith, editors, {\em Maximum-Entropy and
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63 Bayesian Methods in Science and Engineering}. Kluwer Academic, 1988.
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64
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65 \bibitem[Mey67]{Meyer67}
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66 Leonard~B. Meyer.
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67 \newblock {\em Music, the arts and ideas: Patterns and Predictions in
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68 Twentieth-century culture}.
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69 \newblock University of Chicago Press, 1967.
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70
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71 \bibitem[Mol66]{Moles66}
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72 Abraham Moles.
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73 \newblock {\em Information Theory and Esthetic Perception}.
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74 \newblock University of Illinois Press, 1966.
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75
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76 \bibitem[Nar77]{Narmour77}
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77 Eugene Narmour.
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78 \newblock {\em Beyond Schenkerism}.
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79 \newblock University of Chicago Press, 1977.
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80
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81 \bibitem[Pea05]{Pearce2005}
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82 Marcus~T. Pearce.
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83 \newblock {\em The Construction and Evaluation of Statistical Models of Melodic
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84 Structure in Music Perception and Composition}.
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85 \newblock PhD thesis, Department of Computing, City University, London, 2005.
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86
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87 \bibitem[SJAN99]{SaffranJohnsonAslin1999}
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88 J.~R. Saffran, E.~K. Johnson, R.~N. Aslin, and E.~L. Newport.
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89 \newblock Statistical learning of tone sequences by human infants and adults.
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90 \newblock {\em Cognition}, 70(1):27--52, 1999.
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91
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92 \bibitem[VW06]{VerduWeissman2006}
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93 S.~Verd{\'u} and T~Weissman.
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94 \newblock Erasure entropy.
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95 \newblock In {\em IEEE International Symposium on Information Theory (ISIT
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96 2006)}, pages 98--102, 2006.
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97
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98 \bibitem[Wun97]{Wundt1897}
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99 W.~Wundt.
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100 \newblock {\em Outlines of Psychology}.
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101 \newblock Englemann, Lepzig, 1897.
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102
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103 \end{thebibliography}
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