Cognitive musicology
Encyclopedia
Cognitive musicology is a branch of Cognitive Science
concerned with computationally modeling musical knowledge with the goal of understanding both music and cognition. More broadly, it can be considered the set of all phenomena surrounding computational modeling of musical thought and action.
Cognitive musicology can be differentiated from the better known field of Music Cognition
by a difference in methodological emphasis. Cognitive musicology uses computer modeling to study music-related knowledge representation
and has roots in Artificial Intelligence
and Cognitive Science
. The use of computer models provides an exacting, interactive medium in which to formulate and test theories
This interdisciplinary field investigates topics such as the parallels between language and music in the brain. Biologically inspired models of computation are often included in research, such as neural networks and evolutionary programs. This field seeks to model how musical knowledge is represented, stored, perceived, performed, and generated. By using a well-structured computer environment, the systematic structures of these cognitive phenomena can be investigated.
Cognitive musicology is a branch of Cognitive Science
concerned with computationally modeling musical knowledge with the goal of understanding both music and cognition. More broadly, it can be considered the set of all phenomena surrounding computational modeling of musical thought and action.
Cognitive musicology can be differentiated from the better known field of Music Cognition
by a difference in methodological emphasis. Cognitive musicology uses computer modeling to study music-related knowledge representation
and has roots in Artificial Intelligence
and Cognitive Science
. The use of computer models provides an exacting, interactive medium in which to formulate and test theories
This interdisciplinary field investigates topics such as the parallels between language and music in the brain. Biologically inspired models of computation are often included in research, such as neural networks and evolutionary programs. This field seeks to model how musical knowledge is represented, stored, perceived, performed, and generated. By using a well-structured computer environment, the systematic structures of these cognitive phenomena can be investigated.
Cognitive musicology is a branch of Cognitive Science
concerned with computationally modeling musical knowledge with the goal of understanding both music and cognition. More broadly, it can be considered the set of all phenomena surrounding computational modeling of musical thought and action.
Cognitive musicology can be differentiated from the better known field of Music Cognition
by a difference in methodological emphasis. Cognitive musicology uses computer modeling to study music-related knowledge representation
and has roots in Artificial Intelligence
and Cognitive Science
. The use of computer models provides an exacting, interactive medium in which to formulate and test theories
This interdisciplinary field investigates topics such as the parallels between language and music in the brain. Biologically inspired models of computation are often included in research, such as neural networks and evolutionary programs. This field seeks to model how musical knowledge is represented, stored, perceived, performed, and generated. By using a well-structured computer environment, the systematic structures of these cognitive phenomena can be investigated.
, who coined the term "cognitive science", is one of the pioneers of cognitive musicology. Among other things, he is noted for the computational implementation of an early key-finding algorithm . Key finding is an essential element of tonal music, and the key-finding problem has attracted considerable attention in the psychology of music over the past several decades. Carol Krumhansl proposed an empirically grounded key-finding algorithm which bears her name . Her approach is based on key-profiles which she painstakingly determined by what has come to be known as the probe-tone technique . David Temperley, whose early work within the field of cognitive musicology applied dynamic programming to aspects of music cognition, has suggested a number of refinements to the Krumhansl Key-Finding Algorithm .
Otto Laske was a champion of cognitive musicology . A collection of papers that he co-edited served to highten the visibility of cognitive musicology and to strengthen its association with AI and music . The forward of this book reprints a free-wheeling interview with Marvin Minsky, one of the founding fathers of AI, in which he discusses some of his early writings on music and the mind . AI researcher turned cognitive scientist Douglas Hofstadter has also contributed a number of ideas pertaining to music from an AI perspective . Musician Steve Larson, who worked for a time in Hofstadter's lab, formulated a theory of "musical forces" derived by analogy with physical forces . Hofstadter also weighed in on David Cope's experiments in musical intelligence , which take the form of a computer program called EMI which produces music in the form of, say, Bach, or Chopin, or Cope.
Cope's programs are written in Lisp, which turns out to be a popular language for research in cognitive musicology. Desain and Honing have exploited Lisp in their efforts to tap the potential of microworld methodology in cognitive musicology research . Also working in Lisp, Heinrich Taube has explored computer composition from a wide variety of perspectives. There are, of course, researchers who chose to use languages other than Lisp for their research into the computational modeling of musical processes. Tim Rowe, for example, explores "machine musicianship" through C++ programming . A rather different computational methodology for researching musical phenomena is the toolkit approach advocated by David Huron . At a higher level of abstraction, Gerraint Wiggins has investigated general properties of music knowledge representations such as structural generality and expressive completeness .
Although a great deal of cognitive musicology research features symbolic computation, notable contributions have been made from the biologically inspired computational paradigms. For example, Jamshed Bharucha
and Peter Todd have modeled music perception in tonal music with neural networks . Al Biles has applied genetic algorithms to the composition of jazz solos . Numerous researchers have explored algorithmic composition grounded in a wide range of mathematical formalisms .
Within cognitive psychology
, among the most prominent researchers is Diana Deutsch
, who has engaged in a wide variety of work ranging from studies of absolute pitch and musical illusions to the formulation of musical knowledge representations to relationships between music and language . Equally important is Aniruddh Patel, whose work combines traditional methodologies of cognitive psychology with neuroscience
. Patel is also the author of a comprehensive survey of cognitive science research on music.
Perhaps the most significant contribution to viewing music from a linguistic perspective is the Generative Theory of Tonal Music (GTTM) proposed by Fred Lerdahl
and Ray Jackendoff
. Although GTTM is presented at the algorithmic level of abstraction rather than the implementational level, their ideas have found computational manifestations in a number of computational projects .
. A generative science is an interdisciplinary field of study that explores how the world works through research into specific topics. By studying a given topic from a generative perspective, we can see how it functions with natural laws. By studying cognitive musicology, we can potentially understand how humans think about music and how we can computationally model those thoughts.
Cognitive science
Cognitive science is the interdisciplinary scientific study of mind and its processes. It examines what cognition is, what it does and how it works. It includes research on how information is processed , represented, and transformed in behaviour, nervous system or machine...
concerned with computationally modeling musical knowledge with the goal of understanding both music and cognition. More broadly, it can be considered the set of all phenomena surrounding computational modeling of musical thought and action.
Cognitive musicology can be differentiated from the better known field of Music Cognition
Music cognition
Music cognition is an interdisciplinary approach to understanding the mental processes that support musical behaviors, including perception, comprehension, memory, attention, and performance...
by a difference in methodological emphasis. Cognitive musicology uses computer modeling to study music-related knowledge representation
Knowledge representation
Knowledge representation is an area of artificial intelligence research aimed at representing knowledge in symbols to facilitate inferencing from those knowledge elements, creating new elements of knowledge...
and has roots in Artificial Intelligence
Artificial intelligence
Artificial intelligence is the intelligence of machines and the branch of computer science that aims to create it. AI textbooks define the field as "the study and design of intelligent agents" where an intelligent agent is a system that perceives its environment and takes actions that maximize its...
and Cognitive Science
Cognitive science
Cognitive science is the interdisciplinary scientific study of mind and its processes. It examines what cognition is, what it does and how it works. It includes research on how information is processed , represented, and transformed in behaviour, nervous system or machine...
. The use of computer models provides an exacting, interactive medium in which to formulate and test theories
This interdisciplinary field investigates topics such as the parallels between language and music in the brain. Biologically inspired models of computation are often included in research, such as neural networks and evolutionary programs. This field seeks to model how musical knowledge is represented, stored, perceived, performed, and generated. By using a well-structured computer environment, the systematic structures of these cognitive phenomena can be investigated.
Cognitive musicology is a branch of Cognitive Science
Cognitive science
Cognitive science is the interdisciplinary scientific study of mind and its processes. It examines what cognition is, what it does and how it works. It includes research on how information is processed , represented, and transformed in behaviour, nervous system or machine...
concerned with computationally modeling musical knowledge with the goal of understanding both music and cognition. More broadly, it can be considered the set of all phenomena surrounding computational modeling of musical thought and action.
Cognitive musicology can be differentiated from the better known field of Music Cognition
Music cognition
Music cognition is an interdisciplinary approach to understanding the mental processes that support musical behaviors, including perception, comprehension, memory, attention, and performance...
by a difference in methodological emphasis. Cognitive musicology uses computer modeling to study music-related knowledge representation
Knowledge representation
Knowledge representation is an area of artificial intelligence research aimed at representing knowledge in symbols to facilitate inferencing from those knowledge elements, creating new elements of knowledge...
and has roots in Artificial Intelligence
Artificial intelligence
Artificial intelligence is the intelligence of machines and the branch of computer science that aims to create it. AI textbooks define the field as "the study and design of intelligent agents" where an intelligent agent is a system that perceives its environment and takes actions that maximize its...
and Cognitive Science
Cognitive science
Cognitive science is the interdisciplinary scientific study of mind and its processes. It examines what cognition is, what it does and how it works. It includes research on how information is processed , represented, and transformed in behaviour, nervous system or machine...
. The use of computer models provides an exacting, interactive medium in which to formulate and test theories
This interdisciplinary field investigates topics such as the parallels between language and music in the brain. Biologically inspired models of computation are often included in research, such as neural networks and evolutionary programs. This field seeks to model how musical knowledge is represented, stored, perceived, performed, and generated. By using a well-structured computer environment, the systematic structures of these cognitive phenomena can be investigated.
Cognitive musicology is a branch of Cognitive Science
Cognitive science
Cognitive science is the interdisciplinary scientific study of mind and its processes. It examines what cognition is, what it does and how it works. It includes research on how information is processed , represented, and transformed in behaviour, nervous system or machine...
concerned with computationally modeling musical knowledge with the goal of understanding both music and cognition. More broadly, it can be considered the set of all phenomena surrounding computational modeling of musical thought and action.
Cognitive musicology can be differentiated from the better known field of Music Cognition
Music cognition
Music cognition is an interdisciplinary approach to understanding the mental processes that support musical behaviors, including perception, comprehension, memory, attention, and performance...
by a difference in methodological emphasis. Cognitive musicology uses computer modeling to study music-related knowledge representation
Knowledge representation
Knowledge representation is an area of artificial intelligence research aimed at representing knowledge in symbols to facilitate inferencing from those knowledge elements, creating new elements of knowledge...
and has roots in Artificial Intelligence
Artificial intelligence
Artificial intelligence is the intelligence of machines and the branch of computer science that aims to create it. AI textbooks define the field as "the study and design of intelligent agents" where an intelligent agent is a system that perceives its environment and takes actions that maximize its...
and Cognitive Science
Cognitive science
Cognitive science is the interdisciplinary scientific study of mind and its processes. It examines what cognition is, what it does and how it works. It includes research on how information is processed , represented, and transformed in behaviour, nervous system or machine...
. The use of computer models provides an exacting, interactive medium in which to formulate and test theories
This interdisciplinary field investigates topics such as the parallels between language and music in the brain. Biologically inspired models of computation are often included in research, such as neural networks and evolutionary programs. This field seeks to model how musical knowledge is represented, stored, perceived, performed, and generated. By using a well-structured computer environment, the systematic structures of these cognitive phenomena can be investigated.
Notable researchers
The polymath Christopher Longuet-HigginsH. Christopher Longuet-Higgins
Hugh Christopher Longuet-Higgins FRS was both a theoretical chemist and a cognitive scientist. He was born on April 11, 1923 in Kent, England and died on March 27, 2004....
, who coined the term "cognitive science", is one of the pioneers of cognitive musicology. Among other things, he is noted for the computational implementation of an early key-finding algorithm . Key finding is an essential element of tonal music, and the key-finding problem has attracted considerable attention in the psychology of music over the past several decades. Carol Krumhansl proposed an empirically grounded key-finding algorithm which bears her name . Her approach is based on key-profiles which she painstakingly determined by what has come to be known as the probe-tone technique . David Temperley, whose early work within the field of cognitive musicology applied dynamic programming to aspects of music cognition, has suggested a number of refinements to the Krumhansl Key-Finding Algorithm .
Otto Laske was a champion of cognitive musicology . A collection of papers that he co-edited served to highten the visibility of cognitive musicology and to strengthen its association with AI and music . The forward of this book reprints a free-wheeling interview with Marvin Minsky, one of the founding fathers of AI, in which he discusses some of his early writings on music and the mind . AI researcher turned cognitive scientist Douglas Hofstadter has also contributed a number of ideas pertaining to music from an AI perspective . Musician Steve Larson, who worked for a time in Hofstadter's lab, formulated a theory of "musical forces" derived by analogy with physical forces . Hofstadter also weighed in on David Cope's experiments in musical intelligence , which take the form of a computer program called EMI which produces music in the form of, say, Bach, or Chopin, or Cope.
Cope's programs are written in Lisp, which turns out to be a popular language for research in cognitive musicology. Desain and Honing have exploited Lisp in their efforts to tap the potential of microworld methodology in cognitive musicology research . Also working in Lisp, Heinrich Taube has explored computer composition from a wide variety of perspectives. There are, of course, researchers who chose to use languages other than Lisp for their research into the computational modeling of musical processes. Tim Rowe, for example, explores "machine musicianship" through C++ programming . A rather different computational methodology for researching musical phenomena is the toolkit approach advocated by David Huron . At a higher level of abstraction, Gerraint Wiggins has investigated general properties of music knowledge representations such as structural generality and expressive completeness .
Although a great deal of cognitive musicology research features symbolic computation, notable contributions have been made from the biologically inspired computational paradigms. For example, Jamshed Bharucha
Jamshed Bharucha
Jamshed Bharucha is President of Cooper Union. Prior to this, he was Provost and Senior Vice President of Tufts University and Professor in the Departments of Psychology, Music and in the Medical School's Department of Neuroscience...
and Peter Todd have modeled music perception in tonal music with neural networks . Al Biles has applied genetic algorithms to the composition of jazz solos . Numerous researchers have explored algorithmic composition grounded in a wide range of mathematical formalisms .
Within cognitive psychology
Cognitive psychology
Cognitive psychology is a subdiscipline of psychology exploring internal mental processes.It is the study of how people perceive, remember, think, speak, and solve problems.Cognitive psychology differs from previous psychological approaches in two key ways....
, among the most prominent researchers is Diana Deutsch
Diana Deutsch
Diana Deutsch is a British-American perceptual and cognitive psychologist, born in London, England. She is currently Professor of Psychology at the University of California, San Diego, and is one of the most prominent researchers on the psychology of music...
, who has engaged in a wide variety of work ranging from studies of absolute pitch and musical illusions to the formulation of musical knowledge representations to relationships between music and language . Equally important is Aniruddh Patel, whose work combines traditional methodologies of cognitive psychology with neuroscience
Neuroscience
Neuroscience is the scientific study of the nervous system. Traditionally, neuroscience has been seen as a branch of biology. However, it is currently an interdisciplinary science that collaborates with other fields such as chemistry, computer science, engineering, linguistics, mathematics,...
. Patel is also the author of a comprehensive survey of cognitive science research on music.
Perhaps the most significant contribution to viewing music from a linguistic perspective is the Generative Theory of Tonal Music (GTTM) proposed by Fred Lerdahl
Fred Lerdahl
Alfred Whitford Lerdahl is the Fritz Reiner Professor of Musical Composition at Columbia University, and a composer and music theorist best known for his work on pitch space and cognitive constraints on compositional systems or "musical grammar[s]." He has written many orchestral and chamber...
and Ray Jackendoff
Ray Jackendoff
Ray Jackendoff is an American linguist. He is professor of philosophy, Seth Merrin Chair in the Humanities and, with Daniel Dennett, Co-director of the Center for Cognitive Studies at Tufts University...
. Although GTTM is presented at the algorithmic level of abstraction rather than the implementational level, their ideas have found computational manifestations in a number of computational projects .
Generative science
Cognitive Musicology falls within the realm of the generative sciencesGenerative sciences
The generative science is a interdisciplinary and multidisciplinary science that explores the natural world and its complex behaviours as a generative process...
. A generative science is an interdisciplinary field of study that explores how the world works through research into specific topics. By studying a given topic from a generative perspective, we can see how it functions with natural laws. By studying cognitive musicology, we can potentially understand how humans think about music and how we can computationally model those thoughts.
Further reading
- Seifert, Uwe (2010): Investigating the Musical Mind: Situated Cognition, Artistic Human-Robot Interaction Design, and Cognitive Musicology (English/Korean). In: Principles of Media Convergence in the Digital Age. Proceedings of the EWHA HK International Conference 2010, pp. 61–82.
- Seifert, Uwe (1991): The Schema Concept: A Critical Review of its Development and Current Use in Cognitive Science and Research on Music Perception. In: A. Camurri/C. Canepa (Eds.), Proceedings of the IX CIM Colloquium on Musical Informatics, Genova: AIMI/DIST, pp. 116–131.
- Aiello, R., & Sloboda, J. (1994). Musical perceptions. Oxford Oxfordshire: Oxford University Press. —A balanced collection of papers by some of the leading figures in the field of music perception and cognition. Opening chapters on emotion and meaning in music (by Leonard B. Meyer) and the Music as Language metaphor (Rita Aiello) are followed by a range of insightful papers on the perception of music by Niclolous Cook, W. Jay Downling, Jamshed Baruscha, and others.
- Levitin, D. (2007). This is your brain on music. New York: Plume. —Recording engineer turned music psychologist Daniel Levitin talks about the psychology of music in an up tempo, informal, and personal way. Examples drawn from rock and related genres and the limited use of technical terms are two features of the book that make the book appealing to a wide audience.
- Jourdain, R. (1997). Music, the brain, and ecstasy. New York: Harper Collins. —A far-reaching study of how music captivates us so completely and why we form such powerful connections to it. Leading us to an understanding of the pleasures of sound, Robert Jourdain draws on a variety of fields including science, psychology, and philosophy.
External links
- The 1999 Ernest Bloch Lectures delivered by David Huron
- Dr. Otto Laske Webpage
- The Science of Music
- A talk by Brian Eno on Generative Music
- A cool collection of web-based algorithmic composition toys
- Gestalt and Cognitive Musicology
- Music Cognition at Neuroscience for Kids
- Music, Mind, Machine Research Group at Radboud University
- Music Cognition Research Center
- A collection of articles on AI and music
- The Science and Music Group