The role of expectation and probabilistic learning in auditory boundary perception: A model comparison

Perception

Volumn 39, Issue 10, 2010, Pages 1367-1391

  Pearce, Marcus T ^a   Müllensiefen, Daniel ^a   Wiggins, Geraint A ^a  

^a UNIVERSITY OF LONDON   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 78549282728     PISSN: 03010066     EISSN: None     Source Type: Journal    
DOI: 10.1068/p6507     Document Type: Article

References (80)

1. Abdallah S A, Plumbley M D, 2009 Information dynamics: Patterns of expectation and surprise in the perception of music Convection Science 21 89-117
2. Attneave F, 1959 Applications of Information Theory to Psychology (New York: Holt)
3. Balcetis E, Dunning D, 2006 See what you want to see: Motivational influences on visual perception Journal of Personality and Social Psychology 91 612-625
4. Barlow H B, 1959 Sensory mechanisms, the reduction of redundancy, and intelligence, in Proceedings of a Symposium on the Mechanisation of Thought Processes (London: Natural Physical Laboratory, Teddingtonö London: Her Majesty's Stationery Office) pp 537-559
5. Bod R, 1998 Beyond Grammar: An Experience-based Theory of Language (Stanford, CA: CSLI Publications)
6. Bod R, 2001 Memory-based models of melodic analysis: Challenging the Gestalt principles Journal of New Music Research 30 27-37
7. Bower G, 1970 Organizational factors in memory Cognitive Psychology 1 18-46
8. Bregman A S, 1990 Auditory Scene Analysis (Cambridge, MA: MIT Press)
9. Brent M R, 1999a An efficient, probabilistically sound algorithm for segmentation and word discovery Machine Learning 34 71-105
10. Brent M R, 1999b Speech segmentation and word discovery: A computational perspective Trends in Cognitive Sciences 3 294-301
11. Brochard R, Dufour A, Drake C, Scheiber C, 2000 Functional brain imaging of rhythm perception, in Proceedings of the Sixth International Conference of Music Perception and Cognition Eds C Woods, G Luck, R Brochard, F Seddon, J A Sloboda (Keele: University of Keele)
12. Bruce V, Green P, Georgeson M, 2003 Visual Perception: Physiology, Psychology and Ecology (London: Psychology Press)
13. Bruderer M J, 2008 Perception and Modeling of Segment Boundaries in Popular Music PhD thesis, JF Schouten School for User-System Interaction Research, Technische Universiteit Eindhoven, The Netherlands
14. Cambouropoulos E, 2001 The local boundary detection model (LBDM) and its application in the study of expressive timing, in Proceedings of the International Computer Music Conference (San Francisco, CA: ICMA) pp 17-22
15. Cambouropoulos E, 2006 Musical parallelism and melodic segmentation: A computational approach Music Perception 23 249-269
16. Chater N, 1996 Reconciling simplicity and likelihood principles in perceptual organisation Psychological Review 103 566-581
17. Chater N, 1999 The search for simplicity: A fundamental cognitive principle? Quarterly Journal of Experimental Psychology A 52 273-302
18. Clarke E F, Krumhansl K L, 1990 Perceiving musical time Music Perception 7 213-252
19. Cohen P R, Adams N, Heeringa B, 2007 Voting experts: An unsupervised algorithm for segmenting sequences Intelligent Data Analsis 11 607-625
20. Deli ege I, 1987 Grouping conditions in listening to music: An approach to Lerdahl and Jackendoff's grouping preference rules Music Perception 4 325-360
21. Deliege I, 1998 Wagner alte weise': Une approche perceptive Musica Scientia Special Issue 63-90
22. Dowling W J, 1973 Rhythmic groups and subjective chunks in memory for melodies Perception & Psychophysics 14 37-40
23. Elman J L, 1990 Finding structure in time Cognitive Science 14 179-211
24. Everitt B S, Dunn G, 2001 Applied Multivariate Data Analysis (London: Hodder Arnold)
25. Ferrand M, Nelson P, Wiggins G, 2003 Unsupervised learning of melodic segmentation: A memorybased approach, in Proceedings of the 5th Triennial ESCOM Conference Eds R Kopiez, AC Lehmann, I Wolther, C Wolf (Hanover: Hanover University of Music and Drama)pp 141-144
26. Fleiss J L, 1971 Measuring nominal scale agreement among many raters Psychological Bulletin 76378-382
27. Fodor J A, Bever T G, 1965 The psychological reality of linguistic segments Journal of Verbal Learning and Verbal Behavior 4 414-420
28. Frankland B W, Cohen A J, 2004 Parsing of melody: Quantification and testing of the local grouping rules of Lerdahl and Jackendoff's A GenerativeTheory of Tonal Music Music Perception 21 499-543
29. Friston K, 2010 The free-energy principle: a unified brain theory? Nature Reviews Neuroscience 11 127-138
30. Goldwater S, 2007 Nonparametric Bayesian Models of Lexical Acquisition PhD thesis, Department of Cognitive and Linguistic Sciences, Brown University, Providence, USA
31. Gregory A H, 1978 Perception of clicks in music Perception & Psychophysics 24 171-174
32. Hale J, 2006 Uncertainty about the rest of the sentence Cognitive Science 30 643-672
33. Itti L, Baldi P, 2006 Bayesian surprise attracts human attention, in Advances in Neural Information Processing Systems 18 Eds Y Weiss, B Scholkopf, J Platt (Cambridge, MA: MIT Press) pp 547-554
34. Jusczyk P W, 1997 The Discovery of Spoken Language (Cambridge, MA: MIT Press)
35. Jusczyk P W, Krumhansl C L, 1993 Pitch and rhythmic patterns affecting infant's sensitivity to musical phrase structure Journal of Experimental Psychology: Human Perception and Performance 19 627-640
36. Koffka K, 1935 Principles of Gestalt Psychology (New York: Harcourt, Brace and World)
37. Krumhansl C L, 1990 Cognitive Foundations of Musical Pitch (Oxford: Oxford University Press)
38. Kulczynski S, 1927 Die Planzenassoziationen der Pienien Bulletin International de l'Academie Polonaise des Sciences et des Lettres, Classe des Sciences Mathematiques et Naturelles B 57-203
39. Kurby C A, Zacks J M, 2007 Segmentation in the perception and memory of events Trends in Cognitive Sciences 12 72-79
40. Ladefoged P, Broadbent D E, 1960 Perception of sequences in auditory events Journal of Experimental Psychology 12 162-170
41. Landis J R, Koch G G, 1977 The measurement of observer agreement for categorical data Biometrics 33 159-174
42. Leopold D A, Logothetis N K, 1999 Multistable phenomena: changing views in perception Trends in Cognitive Sciences 3 254-264
43. Lerdahl F, Jackendoff R, 1983 A Generative Theory of Tonal Music (Cambridge, MA: MIT Press)
44. Levy R, 2008 Expectation-based syntactic comprehension Cognition 16 1126-1177
45. Liegeoise-Chauvel C, Peretz I, Babai M, Laguitton V, Chauvel P, 1998 Contribution of different cortical areas in the temporal lobes to music processing Brain 121 1853-1867
46. McAdams S, Winsberg S, Donnadieu S, Soete G D, Krimphoff J, 1995 Perceptual scaling of synthesized musical timbres: Common dimensions, specificities and latent subject classes Psychological Research 58 177-192
47. MacKay D J C, 2003 Information Theory, Inference, and Learning Algorithms (Cambridge, UK: Cambridge University Press)
48. Manning C D, Schutze H, 1999 Foundations of Statistical Natural Language Processing (Cambridge, MA: MIT Press)
49. Marr D, 1982 Vision (San Francisco, CA: W H Freeman)
50. Melucci M, Orio N, 2002 A comparison of manual and automatic melody segmentation, in Proceedings of the Third International Conference on Music Information Retrieval Ed. M Fingerhut (Paris: IRCAM) pp 7-14
51. Meyer L B, 1957 Meaning in music and information theory Journal of Aesthetics and Art Criticism 15 412-424
52. Narmour E, 1990 The Analysis and Cognition of Basic Melodic Structures: The Implication-realisation Model (Chicago: University of Chicago Press)
53. Newtson D, 1973 Attribution and the unit of perception of ongoing behavior Journal of Personality and Social Psychology 28 28-38
54. Nooijer J de, Wiering F, Volk A, Tabachneck-Schijf H J M, 2008 An experimental comparison of human and automatic music segmentation, in Proceedings of the 10th International Conference on Music Perception and Cognition Eds K Miyazaki, M Adachi,Y Hiraga, Y Nakajima, M Tsuzaki (Adelaide, Australia: Causal Productions) pp 399-407
55. Pearce M T, Conklin D, Wiggins G A, 2005 Methods for combining statistical models of music, in Computer Music Modelling and Retrieval Ed. U K Wiil (Berlin: Springer) pp 95-312
56. Pearce M T, Mullensiefen D, Wiggins G A, 2010a Melodic grouping in music information retrieval: New methods and applications, in Advances in Music Information Retrieval Eds Z W Ras, A Wieczorkowska (Berlin: Springer) pp 364-388
57. Pearce M T, Ruiz M H, Kapasi S, Wiggins G A, Bhattacharya J, 2010b Unsupervised statistical learning underpins computational, behavioural and neural manifestations of musical expectation NeuroImage 50 302-313
58. Pearce M T, Wiggins G A, 2004 Improved methods for statistical modelling of monophonic music Journal of New Music Research 33 367-385
59. Pearce M T, Wiggins G A, 2006 Expectation in melody: The influence of context and learning Music Perception 23 377-405
60. Pearlmutter N J, Macdonald M C, 1995 Individual differences and probabilistic constraints in syntactic ambiguity resolution Journal of Memory and Language 34 521-542
61. Peretz I, 1989 Clustering in music: An appraisal of task factors International Journal of Psychology 24 157-178
62. Peretz I, 1990 Processing of local and global musical information by unilateral brain-damaged patients Brain 113 1185-1205
63. Reynolds J R, Zacks J M, Braver T S, 2007 A computational model of event segmentation from perceptual prediction Cognitive Science 31 613-643
64. Saffran J R, 2003 Absolute pitch in infancy and adulthood: The role of tonal structure Developmental Science 6 37-49
65. Saffran J R, Aslin R N, Newport E L, 1996 Statistical learning by 8-month old infants Science 274 1926-1928
66. Saffran J R, Griepentrog G J, 2001 Absolute pitch in infant auditory learning: Evidence for developmental reorganization Developmental Psychology 37 74-85
67. Saffran J R, Johnson E K, Aslin R N, Newport E L, 1999 Statistical learning of tone sequences by human infants and adults Cognition 70 27-52
68. Schaffrath H, 1995 The Essen folksong collection, in Database Containing 6,255 Folksong Transcriptions in the Kern Format and a 34-Page Research Guide [Computer Database] Ed. D Huron (Menlo Park, CA: CCARH)
69. Schellenberg E G, 1997 Simplifying the implication-realisation model of melodic expectancy Music Perception 14 295-318
70. Shannon C E, 1948 A mathematical theory of communication Bell System Technical Journal 27 379-423 and 623-656
71. Sloboda J A, Gregory A H, 1980 The psychological reality of musical segments Canadian Journal of Psychology 34 274-280
72. Smith E C, Lewicki M S, 2006 Efficient auditory coding Nature 439 978-982
73. Spiro N, 2006 A new method for assessing consistency of real-time identification of phrase-parts and its initial application, in Proceedings of the 9th International Conference of Music Perception and Cognition Eds M Baroni, R Addessi, R Caterina, M Costa (Bologna: SMPC and ESCOM) pp 793-800
74. Stoffer T H, 1985 Representation of phrase structure in the perception of music Music Perception 3 191-220
75. Tan N, Aiello R, Bever T G, 1981 Harmonic structure as a determinant of melodic organization Memory and Cognition 9 533-539
76. Temperley D, 2001 The Cognition of Basic Musical Structures (Cambridge, MA: MIT Press)
77. Thom B, Spevak C, Hothker K, 2002 Melodic segmentation: Evaluating the performance of algorithms and musical experts, in Proceedings of the International Computer Music Conference (San Francisco, CA: ICMA) pp 65-72
78. Waugh N, Norman D A, 1965 Primary memory Psychological Review 72 89-104
79. Wiggins G A, 2007 Models of musical similarity Musica Scientia (Discussion Forum 4a) 315-337
80. Wiggins G A, 2010 A cross-domain model: grouping of phonemes into syllables by a model of melodic segmentation, in Proceedings of the International Conference on Music Perception and Cognition Eds S M Demorest, S J Morrison, P S Campbell (Seattle, WA: ICMPC and Causal Productions) page 75