Music 206: Emotions, Style and Meaning…

Reading list with some annotations

Introduction:

Common sense in AI, Minsky’s ideas on Music, role of body in reasoning and Sentics

  1. “The St. ThomasCommon SenseSymposium:Designing Architecturesfor Human-Level Intelligence”, Marvin Minsky, Push Singh, and Aaron Sloman, AI Magazine, 2004
  1. “Music, Mind, and Meaning”, Marvin Minsky, Computer Music Journal, 1981,
  1. “Building Brains for Bodies, Rodney Brooks and Lynn Andrea Stein, Autonomous Robots, 1 (1994)
  1. “Time-Forms, Nature's Generators and Communicators of Emotion”, Manfred Clynes, IEEE International Workshop on Robot and Human Communication, Tokyo, Japan, Sept. 1992.

Decision Making and Mental Models:

Relation between rational behavior and mental models, what are the behavioral aspectsof decision making and alternative models for games theory.

  1. “Decision Making and Problem Solving”, by Herbert A. Simon et al., Research Briefings 1986
  1. “Mental models: a gentle guide for outsiders”, P.N. Johnson-Laird, Vittorio Girotto, and Paolo Legrenzi, 1998
  1. “Behavioural studies of strategicthinking in games”, Colin F. Camerer, TRENDS in Cognitive Sciences Vol.7 No.5 May 2003
  1. “Mental Models and Normal Errors”, Kevin Burns, 2002
  1. Game theory and the Cuban missile crisis”, Steven J. Brams, 2001

Complexity:

Complexity in nature, cognition and music

  1. "The Architecture of Complexity", The Sciences of the Artificial, By Herbert Simon, 1969
  1. “Cognitive complexity and the structure of musical patterns”, Jeff Pressing.
  1. “Complexity measures of musical rhythms”, Shmulevich, I., Povel, D.J. (2000). In P. Desain &L.Windsor, Rhythm perception and production
  1. “Complexity Measures for complex systems and complex objects”, Pablo Funes

Emotions:

Models of Emotions in rationality and in music

  1. “Beyond Shallow Models of Emotion”, Aaron Sloman, Cognitive Processing, Vol. 2, No 1, 2001
  1. “Rationality and the Emotions”, Jon Elster, The Economic Journal, 1996
  1. “Detecting Emotion in Music”, Tao Li and Mitsunori Ogihara, 2003
  1. “Disambiguating Music Emotion using Software Agents”, Dan Yang, WonSook Lee, 2004

Affective Processing:

Algorithms and methods for affect processing

  1. “Digital Processing of Affective Signals”, Jennifer Healey and Rosalind Pickard, ICASSP 98.
  1. “Affective Content Detection using HMMs”, Hang-Bong Kang, MM’03
  1. “Using audio features to model the affective response to music”, Marc Leman, Valery Vermeulen, Liesbeth De Voogdt, Dirk Moelants, ISMA2004
  1. “Composing Affective Music with a Generate and Sense Approach”, Sunjung Kim and Elisabeth André, 2004

Improvisation and Emergence:

  1. “Improvisation: Methods and Models”,in Generative processes in music(ed. J. Sloboda) Oxford University Press 1987
  1. “The Mechanisms of Emergence”, R.K.Sawyer, Philosophy of Social Sciences, 2003
  1. “Improvisational Cultures: Collaborative Emergence andCreativity in Improvisation”, R.K.Sawyer, Mind, Culture and Activity, 2000

Narrative:

  1. “Understanding Narrative is Like Observing Agents”, Guido Boella, Rossana Damiano, and Leonardo Lesmo, AAAI 1999
  1. “Narrative Intelligence”, Michael Mateas and Phoebe Sengers, AAAI 1999
  1. “Notes on the Use of Plan Structures in the Creation of Interactive Plot”, R. Michael Young, AAAI 99
  1. “Improvisation and Narrative”, R.K.Sawyer, Narrative Inquiry, 2002

Style:

Style as surface features and local structures

  1. “Style Machines”, Matthew Brand Aaron Hertzmann, SIGGRAPH 2000
  1. “Machine Learning of Musical Style”, Dubnov and Assayag, Computer Magazine, 2002
  1. “Separating Style and Content”, J.B. Tennenbaum and W.T. Freeman, Adv. In NIPS, 1997
  1. “Style as a Choice of Blending Principles”, Joseph A. Goguen and D. Fox Harrell, 2004

Flow:

Is Flow and alternative for describingartistic experience?

  1. “Quality of Experience in VirtualEnvironments”, Andrea GAGGIOLI, Marta BASSI, Antonella DELLE FAVE, 2003
  1. “Improvisation Planning and Jam Session Design using concepts of Sequence Variation and Flow Experience”, Dubnov and Assayag, 2005

Musical Forces:

Physical metaphors and emotional forces

  1. “Musical Forces and Melodic Expectations: ComparingComputer Models and Experimental Results”, Steve Larson, Music Perception, 2004
  1. “Influences of Large-Scale Form on Continuous Ratings in Response to a Contemporary Piece in a Live Concert Setting”, McAdams et al., Music Perception, 2004
  1. “Structural and Affective Aspects of Music from Statistical Audio Signal Analysis”, Dubnov et al, JASIST 2005

Influential Aspects of Information:

Information that affects the receiver

  1. “Toward a Theory of Information Processing”, Sinan Sinanovi´c and Don H. Johnson, 2004.
  1. “Spectral Anticipations”, Dubnov, 2005

Computational Media Aesthetics:

Semantic gap between features and meaning and its relation to aesthetics

  1. “Bridging the Semantic Gap in Content Management, Systems: Computational Media Aesthetics”, Chitra Dorai, Svetha Venkatesh
  1. “Negotiating the semantic gap: from feature maps to semantic landscapes”, Rong Zhao, W.I. Grosky, Pattern Recognition 35 (2002)
  1. “Where DoesComputationalMedia AestheticsFit?”, Brett Adams, 2003