Towards music perception by redundancy reduction and unsupervised learning in probabilistic models

[1]  R. F. Lyon,et al.  Correlograms and the Separation of Sounds , 1990, 1990 Conference Record Twenty-Fourth Asilomar Conference on Signals, Systems and Computers, 1990..

[2]  S. P. Luttrell,et al.  A Bayesian Analysis of Self-Organizing Maps , 1994, Neural Computation.

[3]  Ian Cross,et al.  Modelling Music as Input-Output and as Process , 1987 .

[4]  Ian H. Witten,et al.  Multiple viewpoint systems for music prediction , 1995 .

[5]  Aapo Hyvärinen,et al.  Topographic Independent Component Analysis , 2001, Neural Computation.

[6]  T J Sejnowski,et al.  Learning the higher-order structure of a natural sound. , 1996, Network.

[7]  J. Cardoso.  Infomax and maximum likelihood for blind source separation , 1997, IEEE Signal Processing Letters.

[8]  Dominik Endres,et al.  Quadratic programming for learning sparse codes , 1999 .

[9]  Marc Leman,et al.  Naturalistic approaches to musical semiotics and the study of causal musical signification , 1999 .

[10]  Simon Dixon,et al.  On the Computer Recognition of Solo Piano Music , 2000 .

[11]  Edward R. Tufte,et al.  Envisioning Information , 1990 .

[12]  Aapo Hyvärinen,et al.  Emergence of Phase- and Shift-Invariant Features by Decomposition of Natural Images into Independent Feature Subspaces , 2000, Neural Computation.

[13]  Boualem Boashash,et al.  Note on the use of the Wigner distribution for time-frequency signal analysis , 1988, IEEE Trans. Acoust. Speech Signal Process..

[14]  Christopher Raphael,et al.  Synthesizing Musical Accompaniments With Bayesian belief networks , 2001 .

[15]  John W. Sammon,et al.  A Nonlinear Mapping for Data Structure Analysis , 1969, IEEE Transactions on Computers.

[16]  Shun-ichi Amari,et al.  Methods of information geometry , 2000 .

[17]  D. Field,et al.  Natural image statistics and efficient coding. , 1996, Network.

[18]  K. Jarrod Millman,et al.  Learning Sparse Codes with a Mixture-of-Gaussians Prior , 1999, NIPS.

[19]  Douglas Keislar,et al.  History and Principles of Microtonal Keyboards , 1987 .

[20]  John F. Kolen,et al.  Resonance and the Perception of Musical Meter , 1994, Connect. Sci..

[21]  Erkki Oja,et al.  Image feature extraction by sparse coding and independent component analysis , 1998, Proceedings. Fourteenth International Conference on Pattern Recognition (Cat. No.98EX170).

[22]  H. B. Barlow,et al.  Unsupervised Learning , 1989, Neural Computation.

[23]  Liubomire G. Iordanov.  The Principal Component Structure of Natural Sound , 1999, NIPS 1999.

[24]  Michael I. Jordan,et al.  Kernel independent component analysis , 2003 .

[25]  Jürgen Schmidhuber,et al.  Learning Unambiguous Reduced Sequence Descriptions , 1991, NIPS.

[26]  J. Pickles.  An Introduction to the Physiology of Hearing , 1982 .

[27]  H. Barlow.  Conditions for versatile learning, Helmholtz's unconscious inference, and the task of perception , 1990, Vision Research.

[28]  Teuvo Kohonen,et al.  Self-organized formation of topologically correct feature maps , 2004, Biological Cybernetics.

[29]  Anssi Klapuri,et al.  AUTOMATIC TRANSCRIPTION OF MUSIC , 2003 .

[30]  Eero P. Simoncelli,et al.  Natural Sound Statistics and Divisive Normalization in the Auditory System , 2000, NIPS.

[31]  R Meddis,et al.  Simulation of auditory-neural transduction: further studies. , 1988, The Journal of the Acoustical Society of America.

[32]  H. C. Longuet-Higgins,et al.  Mental Processes: Studies in Cognitive Science , 1987 .

[33]  J. Risset,et al.  Exploration of timbre by analysis and synthesis , 1999 .

[34]  Jürgen Schmidhuber,et al.  Learning Complex, Extended Sequences Using the Principle of History Compression , 1992, Neural Computation.

[35]  Joseph J. Atick,et al.  Towards a Theory of Early Visual Processing , 1990, Neural Computation.

[36]  P. Földiák,et al.  Forming sparse representations by local anti-Hebbian learning , 1990, Biological Cybernetics.

[37]  Judea Pearl,et al.  Probabilistic reasoning in intelligent systems - networks of plausible inference , 1991, Morgan Kaufmann series in representation and reasoning.

[38]  Stephanie Seneff.  Pitch and spectral estimation of speech based on auditory synchrony model , 1984, ICASSP.

[39]  J. Fodor.  The Modularity of mind. An essay on faculty psychology , 1986 .

[40]  Juha Karhunen,et al.  Neural approaches to independent component analysis and source separation , 1996, ESANN.

[41]  M. Kendall.  Probability and Statistical Inference , 1956, Nature.

[42]  Louis P. DiPalma,et al.  Music and Connectionism , 1991 .

[43]  Roy D. Patterson,et al.  SVOS final report : The auditory filterbank , 1988 .

[44]  J. Gibson.  The Ecological Approach to Visual Perception , 1979 .

[45]  C. Chui.  Wavelets: A Mathematical Tool for Signal Analysis , 1997 .

[46]  Michael A. Casey,et al.  Auditory group theory with applications to statistical basis methods for structured audio , 1998 .

[47]  Yee Whye Teh,et al.  A New View of ICA , 2001 .

[48]  Daniel P. W. Ellis,et al.  Mid-level representations for Computational Auditory Scene Analysis , 1995, IJCAI 1995.

[49]  M. Puckette,et al.  Calculation of a "narrowed" autocorrelation function. , 1989, The Journal of the Acoustical Society of America.

[50]  J. Nadal,et al.  Nonlinear neurons in the low-noise limit: a factorial code maximizes information transfer Network 5 , 1994 .

[51]  Erkki Oja,et al.  A fast algorithm for estimating overcomplete ICA bases for image windows , 1999, IJCNN'99. International Joint Conference on Neural Networks. Proceedings (Cat. No.99CH36339).

[52]  Terrence J. Sejnowski,et al.  The “independent components” of natural scenes are edge filters , 1997, Vision Research.

[53]  Simon Dixon,et al.  Automatic Extraction of Tempo and Beat From Expressive Performances , 2001 .

[54]  A. Schoenberg,et al.  Structural functions of harmony , 1954 .

[55]  Ernst Mach,et al.  The Analysis of Sensations. , 1916 .

[56]  W. L. Windsor,et al.  A perceptual approach to the description and analysis of acousmatic music , 1995 .

[57]  F ATTNEAVE,et al.  Dimensions of similarity. , 1950, The American journal of psychology.

[58]  J. Gibson.  The Senses Considered As Perceptual Systems , 1967 .

[59]  L. Cohen,et al.  Time-frequency distributions-a review , 1989, Proc. IEEE.

[60]  Daniel Patrick Whittlesey Ellis,et al.  Prediction-driven computational auditory scene analysis , 1996 .

[61]  Robert Cowell,et al.  Introduction to Inference for Bayesian Networks , 1998, Learning in Graphical Models.

[62]  W. Köhler.  Gestalt psychology , 1967 .

[63]  G. A. Miller,et al.  Statistical behavioristics and sequences of responses. , 1949, Psychological review.

[64]  J Lazzaro,et al.  Silicon modeling of pitch perception. , 1989, Proceedings of the National Academy of Sciences of the United States of America.

[65]  A. Hyvärinen,et al.  A multi-layer sparse coding network learns contour coding from natural images , 2002, Vision Research.

[66]  Reinier Plomp,et al.  Aspects of tone sensation , 1976 .

[67]  Roger Shepard.  Cognitive psychology and music , 1999 .

[68]  Christopher M. Bishop.  Latent Variable Models , 1998, Learning in Graphical Models.

[69]  Michael I. Jordan,et al.  An Introduction to Variational Methods for Graphical Models , 1999, Machine Learning.

[70]  Pierre Comon,et al.  Independent component analysis, A new concept? , 1994, Signal Process..

[71]  Eero P. Simoncelli.  Modeling the joint statistics of images in the wavelet domain , 1999, Optics & Photonics.

[72]  Zoubin Ghahramani,et al.  Probabilistic Models for Unsupervised Learning , 1999 .

[73]  George Berkeley,et al.  A treatise concerning the principles of human knowledge, 1734 , 1971 .

[74]  B. Olshausen.  Learning linear, sparse, factorial codes , 1996 .

[75]  F. Attneave.  Some informational aspects of visual perception. , 1954, Psychological review.

[76]  J. Locke.  An Essay concerning Human Understanding , 1924, Nature.

[77]  Peter Földiák,et al.  Adaptation and decorrelation in the cortex , 1989 .

[78]  William J. Williams,et al.  Shift covariant time-frequency distributions of discrete signals , 1999, IEEE Trans. Signal Process..

[79]  Thomas M. Cover,et al.  Elements of Information Theory , 2005 .

[80]  William H. Press,et al.  Numerical recipes in C , 2002 .

[81]  C. Krumhansl,et al.  Tracing the dynamic changes in perceived tonal organization in a spatial representation of musical keys. , 1982, Psychological review.

[82]  Hagai Attias,et al.  Temporal Low-Order Statistics of Natural Sounds , 1996, NIPS.

[83]  Jean-François Cardoso,et al.  Equivariant adaptive source separation , 1996, IEEE Trans. Signal Process..

[84]  William D. Penny,et al.  Mixtures of Independent Component Analysers , 2001, ICANN.

[85]  W. Torgerson.  Multidimensional scaling: I. Theory and method , 1952 .

[86]  D. Gabor.  Acoustical Quanta and the Theory of Hearing , 1947, Nature.

[87]  D. Rubin,et al.  Maximum likelihood from incomplete data via the EM - algorithm plus discussions on the paper , 1977 .

[88]  Guy J. Brown,et al.  A blackboard architecture for computational auditory scene analysis , 1999, Speech Commun..

[89]  R. C. Oldfield,et al.  Memory mechanisms and the theory of schemata. , 1954, The British journal of medical psychology.

[90]  H. Helmholtz.  Helmholtz's Treatise on Physiological Optics , 1963 .

[91]  R. Shepard.  Geometrical approximations to the structure of musical pitch. , 1982, Psychological review.

[92]  Geoffrey E. Hinton,et al.  Adaptive Mixtures of Local Experts , 1991, Neural Computation.

[93]  Jamshed J. Bharucha,et al.  Event hierarchies, tonal hierarchies, and assimilation: A reply to Deutsch and Dowling. , 1984 .

[94]  Oldfield Rc,et al.  MEMORY MECHANISMS AND THE THEORY OF SCHEMATA1 , 1954 .

[95]  Christopher M. Bishop,et al.  GTM: The Generative Topographic Mapping , 1998, Neural Computation.

[96]  G. A. Miller.  What is information measurement , 1953 .

[97]  Diana Raffman,et al.  Language, Music, and Mind , 1993 .

[98]  Emilios Cambouropoulos,et al.  Towards a General Computational Theory of Musical Structure , 1998 .

[99]  D. Deutsch,et al.  The Psychology of Music , 1983 .

[100]  Stéphane Mallat,et al.  Matching pursuits with time-frequency dictionaries , 1993, IEEE Trans. Signal Process..

[101]  Jechang Jeong,et al.  Kernel design for reduced interference distributions , 1992, IEEE Trans. Signal Process..

[102]  Malcolm Slaney,et al.  An Efficient Implementation of the Patterson-Holdsworth Auditory Filter Bank , 1997 .

[103]  Terrence J. Sejnowski,et al.  An Information-Maximization Approach to Blind Separation and Blind Deconvolution , 1995, Neural Computation.

[104]  R. Jackendoff,et al.  A Generative Theory of Tonal Music , 1985 .

[105]  Graeme Mitchison,et al.  A Type of Duality between Self-Organizing Maps and Minimal Wiring , 1995, Neural Computation.

[106]  Richard F. Lyon,et al.  An analog electronic cochlea , 1988, IEEE Trans. Acoust. Speech Signal Process..

[107]  D. Deutsch,et al.  Two issues concerning tonal hierarchies: comment on Castellano, Bharucha, and Krumhansl. , 1984, Journal of experimental psychology. General.

[108]  Richard F. Lyon,et al.  Computational models of neural auditory processing , 1984, ICASSP.

[109]  David J. Field,et al.  What Is the Goal of Sensory Coding? , 1994, Neural Computation.

[110]  L. Shen,et al.  Linear Algebra , 1968 .

[111]  Andrzej Cichocki,et al.  A New Learning Algorithm for Blind Signal Separation , 1995, NIPS.

[112]  David K. Mellinger,et al.  Event formation and separation in musical sound , 1992 .

[113]  Kunio Kashino,et al.  Application of the Bayesian probability network to music scene analysis , 1998 .

[114]  Olivier Rioul,et al.  Affine smoothing of the Wigner-Ville distribution , 1990, International Conference on Acoustics, Speech, and Signal Processing.

[115]  Michael E. Tipping,et al.  Probabilistic Principal Component Analysis , 1999 .

[116]  Refractor.  Vision , 2000, The Lancet.

[117]  Les Atlas,et al.  New properties to alleviate interference in time-frequency representations , 1991, [Proceedings] ICASSP 91: 1991 International Conference on Acoustics, Speech, and Signal Processing.

[118]  Martin J. Wainwright,et al.  Scale Mixtures of Gaussians and the Statistics of Natural Images , 1999, NIPS.

[119]  Terrence J. Sejnowski,et al.  Learning Overcomplete Representations , 2000, Neural Computation.

[120]  David J. Field,et al.  Emergence of simple-cell receptive field properties by learning a sparse code for natural images , 1996, Nature.

[121]  C. Krumhansl.  Cognitive Foundations of Musical Pitch , 1990 .

[122]  Brendan J. Frey,et al.  Graphical Models for Machine Learning and Digital Communication , 1998 .

[123]  A. Norman Redlich,et al.  Redundancy Reduction as a Strategy for Unsupervised Learning , 1993, Neural Computation.

[124]  G. Jameson.  Topology and Normed Spaces , 1974 .

[125]  R. Shaw,et al.  The role of symmetry in event perception. , 1974 .

[126]  Daniel Patrick,et al.  A PERCEPTUAL REPRESENTATION OF AUDIO , 1992 .

[127]  Aapo Hyvärinen,et al.  Emergence of complex cell properties by decomposition of natural images into independent feature subspaces , 1999 .

[128]  Diana Deutsch,et al.  Grouping Mechanisms in Music , 1999 .

[129]  Christian Jutten,et al.  Blind separation of sources, part I: An adaptive algorithm based on neuromimetic architecture , 1991, Signal Process..

[130]  W. R. Garner.  Applications of Information Theory to Psychology , 1959 .

[131]  Peter M. Todd,et al.  The Ontogenesis of Tonal Semantics: Results of a Computer Study , 2003 .

[132]  Peter M. Todd,et al.  Pitch, Harmony, and Neural Nets: A Psychological Perspective , 2003 .

[133]  R. M. Warren.  Perceptual Restoration of Missing Speech Sounds , 1970, Science.