Remember Me
Or use your Academic/Social account:


Or use your Academic/Social account:


You have just completed your registration at OpenAire.

Before you can login to the site, you will need to activate your account. An e-mail will be sent to you with the proper instructions.


Please note that this site is currently undergoing Beta testing.
Any new content you create is not guaranteed to be present to the final version of the site upon release.

Thank you for your patience,
OpenAire Dev Team.

Close This Message


Verify Password:
Verify E-mail:
*All Fields Are Required.
Please Verify You Are Human:
fbtwitterlinkedinvimeoflicker grey 14rssslideshare1
Pearce, Marcus T.; Müllensiefen, Daniel; Wiggins, Geraint (2010)
Publisher: Pion
Languages: English
Types: Article
Grouping and boundary perception are central to many aspects of sensory processing in cognition. We present a comparative study of recently published computational models of boundary perception in music. In doing so, we make three contributions. First, we hypothesise a relationship between expectation and grouping in auditory perception, and introduce a novel information-theoretic model of perceptual segmentation to test the hypothesis. Although we apply the model to musical melody, it is applicable in principle to sequential grouping in other areas of cognition. Second, we address a methodological consideration in the analysis of ambiguous stimuli that produce different percepts between individuals.We propose and demonstrate a solution to this problem, based on clustering of participants prior to analysis. Third, we conduct the first comparative analysis of probabilistic-learning and rule-based models of perceptual grouping in music. In spite of having only unsupervised exposure to music, the model performs comparably to rule-based models based on expert musical knowledge, supporting a role for probabilistic learning in perceptual segmentation of music
  • The results below are discovered through our pilot algorithms. Let us know how we are doing!

    • Abdallah S A, Plumbley M D, 2009 ``Information dynamics: Patterns of expectation and surprise in the perception of music'' Convection Science 21 89 ^ 117
    • Attneave F, 1959 Applications of Information Theory to Psychology (New York: Holt)
    • 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
    • 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
    • Bod R,1998 Beyond Grammar:An Experience-based Theory of Language (Stanford, CA: CSLI Publications)
    • Bod R, 2001 ``Memory-based models of melodic analysis: Challenging the Gestalt principles'' Journal of New Music Research 30 27 ^ 37
    • Bower G, 1970 ``Organizational factors in memory'' Cognitive Psychology 1 18 ^ 46
    • Bregman A S, 1990 Auditory Scene Analysis (Cambridge, MA: MIT Press)
    • Brent M R, 1999a ``An efficient, probabilistically sound algorithm for segmentation and word discovery'' Machine Learning 34 71 ^ 105
    • Brent M R, 1999b ``Speech segmentation and word discovery: A computational perspective'' Trends in Cognitive Sciences 3 294 ^ 301
    • 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)
    • Bruce V, Green P, Georgeson M, 2003 Visual Perception: Physiology, Psychology and Ecology (London: Psychology Press)
    • Bruderer M J, 2008 Perception and Modeling of Segment Boundaries in Popular Music PhD thesis, J F Schouten School for User-System Interaction Research, Technische Universiteit Eindhoven, The Netherlands
    • 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
    • Cambouropoulos E, 2006 ``Musical parallelism and melodic segmentation: A computational approach'' Music Perception 23 249 ^ 269
    • Chater N, 1996 ``Reconciling simplicity and likelihood principles in perceptual organisation'' Psychological Review 103 566 ^ 581
    • Chater N, 1999 ``The search for simplicity: A fundamental cognitive principle? '' Quarterly Journal of Experimental Psychology A 52 273 ^ 302
    • Clarke E F, Krumhansl K L, 1990 ``Perceiving musical time'' Music Perception 7 213 ^ 252
    • Cohen P R, Adams N, Heeringa B, 2007 ``Voting experts: An unsupervised algorithm for segmenting sequences'' Intelligent Data Analysis 11 607 ^ 625
    • Deli e©ge I, 1987 ``Grouping conditions in listening to music: An approach to Lerdahl and Jackendoff's grouping preference rules'' Music Perception 4 325 ^ 360
    • Delie© ge I, 1998 ``Wagner `alte weise': Une approche perceptive'' Music× Scienti× Special Issue 63 ^ 90
    • Dowling W J, 1973 ``Rhythmic groups and subjective chunks in memory for melodies'' Perception & Psychophysics 14 37 ^ 40
    • Elman J L, 1990 ``Finding structure in time'' Cognitive Science 14 179 ^ 211
    • Everitt B S, Dunn G, 2001 Applied Multivariate Data Analysis (London: Hodder Arnold)
    • 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, A C Lehmann, I Wolther, C Wolf (Hanover: Hanover University of Music and Drama) pp 141 ^ 144
    • Fleiss J L, 1971 ``Measuring nominal scale agreement among many raters'' Psychological Bulletin 76 378 ^ 382
    • Fodor J A, Bever T G, 1965 ``The psychological reality of linguistic segments'' Journal of Verbal Learning and Verbal Behavior 4 414 ^ 420
    • Frankland B W, Cohen A J, 2004 ``Parsing of melody: Quantification and testing of the local grouping rules of Lerdahl and Jackendoff's A Generative Theory of Tonal Music'' Music Perception 21 499 ^ 543
    • Friston K, 2010 ``The free-energy principle: a unified brain theory?'' Nature Reviews Neuroscience 11 127 ^ 138
    • Goldwater S, 2007 Nonparametric Bayesian Models of Lexical Acquisition PhD thesis, Department of Cognitive and Linguistic Sciences, Brown University, Providence, USA
    • Gregory A H, 1978 ``Perception of clicks in music'' Perception & Psychophysics 24 171 ^ 174
    • Hale J, 2006 ``Uncertainty about the rest of the sentence'' Cognitive Science 30 643 ^ 672
    • Itti L, Baldi P, 2006 ``Bayesian surprise attracts human attention'', in Advances in Neural Information Processing Systems 18 Eds Y Weiss, B Sch o«lkopf, J Platt (Cambridge, MA: MIT Press) pp 547 ^ 554
    • Jusczyk P W, 1997 The Discovery of Spoken Language (Cambridge, MA: MIT Press)
    • 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
    • Koffka K, 1935 Principles of Gestalt Psychology (New York: Harcourt, Brace and World)
    • Krumhansl C L, 1990 Cognitive Foundations of Musical Pitch (Oxford: Oxford University Press)
    • Kulczynski S, 1927 ``Die Planzenassoziationen der Pienien'' Bulletin International de l'Acade¨ mie Polonaise des Sciences et des Lettres, Classe des Sciences Mathe¨ matiques et Naturelles B 57 ^ 203
    • Kurby C A, Zacks J M, 2007 ``Segmentation in the perception and memory of events'' Trends in Cognitive Sciences 12 72 ^ 79
    • Ladefoged P, Broadbent D E, 1960 ``Perception of sequences in auditory events'' Journal of Experimental Psychology 12 162 ^ 170
    • Landis J R, Koch G G, 1977 ``The measurement of observer agreement for categorical data'' Biometrics 33 159 ^ 174
    • Leopold D A, Logothetis N K, 1999 ``Multistable phenomena: changing views in perception'' Trends in Cognitive Sciences 3 254 ^ 264
    • Lerdahl F, Jackendoff R, 1983 A Generative Theory of Tonal Music (Cambridge, MA: MIT Press)
    • Levy R, 2008 ``Expectation-based syntactic comprehension'' Cognition 16 1126 ^ 1177
    • 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
    • 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
    • MacKay D J C, 2003 Information Theory, Inference, and Learning Algorithms (Cambridge, UK: Cambridge University Press)
    • Manning C D, Schu« tze H, 1999 Foundations of Statistical Natural Language Processing (Cambridge, MA: MIT Press)
    • Marr D, 1982 Vision (San Francisco, CA: W H Freeman)
    • 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
    • Meyer L B, 1957 ``Meaning in music and information theory'' Journal of Aesthetics and Art Criticism 15 412 ^ 424
    • Narmour E, 1990 The Analysis and Cognition of Basic Melodic Structures: The Implication-realisation Model (Chicago: University of Chicago Press)
    • Newtson D, 1973 ``Attribution and the unit of perception of ongoing behavior'' Journal of Personality and Social Psychology 28 28 ^ 38
    • 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
    • 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
    • Pearce M T, Mu« llensiefen 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
    • 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
    • Pearce M T, Wiggins G A, 2004 ``Improved methods for statistical modelling of monophonic music'' Journal of New Music Research 33 367 ^ 385
    • Pearce M T, Wiggins G A, 2006 ``Expectation in melody: The influence of context and learning'' Music Perception 23 377 ^ 405
    • Pearlmutter N J, Macdonald M C, 1995 ``Individual differences and probabilistic constraints in syntactic ambiguity resolution'' Journal of Memory and Language 34 521 ^ 542
    • Peretz I, 1989 ``Clustering in music: An appraisal of task factors'' International Journal of Psychology 24 157 ^ 178
    • Peretz I, 1990 ``Processing of local and global musical information by unilateral brain-damaged patients'' Brain 113 1185 ^ 1205
    • Reynolds J R, Zacks J M, Braver T S, 2007 ``A computational model of event segmentation from perceptual prediction'' Cognitive Science 31 613 ^ 643
    • Saffran J R, 2003 ``Absolute pitch in infancy and adulthood: The role of tonal structure'' Developmental Science 6 37 ^ 49
    • Saffran J R, Aslin R N, Newport E L, 1996 ``Statistical learning by 8-month old infants'' Science 274 1926 ^ 1928
    • Saffran J R, Griepentrog G J, 2001 ``Absolute pitch in infant auditory learning: Evidence for developmental reorganization'' Developmental Psychology 37 74 ^ 85
    • 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
    • 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)
    • Schellenberg E G, 1997 ``Simplifying the implication-realisation model of melodic expectancy'' Music Perception 14 295 ^ 318
    • Shannon C E, 1948 ``A mathematical theory of communication'' Bell System Technical Journal 27 379 ^ 423 and 623 ^ 656
    • Sloboda J A, Gregory A H, 1980 ``The psychological reality of musical segments'' Canadian Journal of Psychology 34 274 ^ 280
    • Smith E C, Lewicki M S, 2006 ``Efficient auditory coding'' Nature 439 978 ^ 982
    • 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
    • Stoffer T H, 1985 ``Representation of phrase structure in the perception of music'' Music Perception 3 191 ^ 220
    • Tan N, Aiello R, Bever T G, 1981 ``Harmonic structure as a determinant of melodic organization'' Memory and Cognition 9 533 ^ 539
    • Temperley D, 2001 The Cognition of Basic Musical Structures (Cambridge, MA: MIT Press)
    • Thom B, Spevak C, Ho« thker 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
    • Waugh N, Norman D A, 1965 ``Primary memory'' Psychological Review 72 89 ^ 104
    • Wiggins G A, 2007 ``Models of musical similarity'' Music× Scienti× (Discussion Forum 4a) 315 ^ 337
    • 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
    • ISSN 0301-0066 (print)
  • No related research data.
  • No similar publications.

Share - Bookmark

Cite this article