Modelling affective-based music compositional intelligence with the aid of ANS analyses

This research investigates the use of emotion data derived from analyzing change in activity in the autonomic nervous system (ANS) as revealed by brainwave production to support the creative music compositional intelligence of an adaptive interface. A relational model of the influence of musical events on the listener's affect is first induced using inductive logic programming paradigms with the emotion data and musical score features as inputs of the induction task. The components of composition such as interval and scale, instrumentation, chord progression and melody are automatically combined using genetic algorithm and melodic transformation heuristics that depend on the predictive knowledge and character of the induced model. Out of the four targeted basic emotional states, namely, stress, joy, sadness, and relaxation, the empirical results reported here show that the system is able to successfully compose tunes that convey one of these affective states.

[1]  Ramón López de Mántaras,et al.  Ai and Music: From Composition to Expressive Performance , 2002, AI Mag..

[2]  Tao Li,et al.  Detecting emotion in music , 2003, ISMIR.

[3]  J. Sloboda.  Music Structure and Emotional Response: Some Empirical Findings , 1991 .

[4]  Isabelle Peretz,et al.  ception and Performance, 26, 1797–1813. Juslin, PN, & Sloboda, JA (2001). Music and emotion: Theory and re-search. New York: Oxford Univer , 2002 .

[5]  Somnuk Phon-Amnuaisuk,et al.  Evolutionary methods for musical composition , 1998 .

[6]  Toshimitsu Musha,et al.  Feature extraction from EEGs associated with emotions , 1997, Artificial Life and Robotics.

[7]  Takehisa Onisawa,et al.  Interactive music composition system - composition of 16-bars musical work with a melody part and backing parts , 2004, 2004 IEEE International Conference on Systems, Man and Cybernetics (IEEE Cat. No.04CH37583).

[8]  Jennifer Healey,et al.  Affective wearables , 1997, Digest of Papers. First International Symposium on Wearable Computers.

[9]  Patrik N. Juslin.  Studies of music performance: A theoretical analysis of empirical findings , 2003 .

[10]  Takehisa Onisawa,et al.  Music composition system based on subjective evaluation , 2003, SMC'03 Conference Proceedings. 2003 IEEE International Conference on Systems, Man and Cybernetics. Conference Theme - System Security and Assurance (Cat. No.03CH37483).

[11]  C B Ferry.  The Autonomic Nervous System , 1967 .

[12]  J. Sloboda,et al.  Music and emotion: Theory and research , 2001 .

[13]  A. Gabrielsson,et al.  The influence of musical structure on emotional expression. , 2001 .

[14]  J. Russell,et al.  The circumplex model of affect: An integrative approach to affective neuroscience, cognitive development, and psychopathology , 2005, Development and Psychopathology.

[15]  Elisabeth André,et al.  Composing Affective Music with a Generate and Sense Approach , 2004, FLAIRS.

[16]  J. R. Quinlan.  Learning Logical Definitions from Relations , 1990 .

[17]  Doug Riecken.  Wolfgang: "emotions" plus goals enable learning , 1998, SMC'98 Conference Proceedings. 1998 IEEE International Conference on Systems, Man, and Cybernetics (Cat. No.98CH36218).

[18]  Masamichi Shimura,et al.  Refining a Relational Theory with Multiple Faults in the Concept and Subconcepts , 1992, ML.

[19]  Masayuki Numao,et al.  Music compositional intelligence with an affective flavor , 2007, IUI '07.

[20]  Masayuki Numao,et al.  An Emotion-Driven Musical Piece Generator for a Constructive Adaptive User Interface , 2006, PRICAI.

[21]  Masayuki Numao,et al.  Learning first-order rules from data with multiple parts: applications on mining chemical compound data , 2004, ICML '04.

[22]  Brad Johanson,et al.  GP-Music: An Interactive Genetic Programming System for Music Generation with Automated Fitness Raters , 2007 .

[23]  Masayuki Numao,et al.  Constructive adaptive user interfaces: composing music based on human feelings , 2002, AAAI/IAAI.

[24]  Anders Friberg,et al.  Emotional Coloring of Computer-Controlled Music Performances , 2000, Computer Music Journal.

[25]  David Rosenboom,et al.  Extended Musical Interface with the Human Nervous System: Assessment and Prospectus , 2017, Leonardo.