Connectionist Models of Musical Thinking
|Author: ||Fiske, Harold E.|
The book explores a series of neural network models designed to represent music listening processes. Backpropagation, Adaptive Resonance Theory, and other connectionist procedures are used to model melodic perception, interpretation, and expression. The history and theory of neural network research is presented, and development and construction of the music models is discussed in sufficient detail to interest both specialists and non-specialists. A series of listening experiments demonstrates the models’ validity. The book considers how neural network models can be used to bridge bottom-up and top-down theories of music perception and cognition in addressing questions such as musical imagery, memory and learning, lateral thinking, context and cultural effects on musical understanding. The outcome is a comprehensive theory of musical thinking and understanding. The book is intended for music researchers and graduate students in the fields of music psychology, artificial intelligence and neural network theory, music theory, music cognitive philosophy, and music education.
“Over the last two decades, Harold Fiske has developed a rigorous and refined theory of music cognition (Fiske 1984, 1990, 1993, 1996). The premise of Fiske’s theory, first introduced in his 1990 publication, Music and Mind, is that music cognition is comprised of decisions made in the classification and comparison of tonal-rhythmic patterns, rather than knowledge about those patterns (e.g. key note, scale degree or meter). Thus, Fiske’s interest is in the procedural knowledge of music cognition rather than in its declarative knowledge, an emphasis that has distinguished his work from that of many other researchers in the field. In effect, Fiske, wielding Occam’s razor, asks the question, “What is left in music cognition once all cultural and historical stylistic features have been removed?” Or, to put it another way, what is the panstylistic, cross-cultural kernel of music cognition? Fiske’s answer is that musical units (tonal-rhythmic patterns) are compared with each other and this comparison process yields three categories of inter-pattern relationship: (1) two patterns are judged to be the same as each other (a P relationship), (2) they are judged to be related to each other (a P’ relationship) or (3) they are judged to different from each other (a Pn relationship). Different listeners may come to different conclusions regarding the relationship between patterns, and their conclusions will be shaped by how many levels of a pattern-comparison hierarchy they are able or choose to negotiate. These inter-individual differences may be determined by, say, aural acuity, memory, or musical training or, more generally, by what facets of a sonic pattern are considered relevant by a given listener in a particular situation. The current volume presents an operationalization of Fiske’s theory as a set of connectionist computer models … the reader will discover in the pages that follow, Harold Fiske, has provided us with a fascinating and appealing theory, deftly operationalized, meticulously modeled and thoroughly tested against human-listener behavior.” – (from the Commendatory Preface) Professor Matthew Royal, University of Western Ontario, London, Ontario
“Dr. Harold Fiske’s fourth book represents a culmination of his more than twenty years of research about music perception and cognition. It is extremely well written as are his prior works. Connectionism or Neural Network Theory is a field upon which one cannot tread lightly. It is very dense and requires some familiarity with mathematical constructs in order to fully understand. (I speak from a musician’s perspective.) Nevertheless, I can say that the main issues and descriptions of the modeling process Fiske describes are clearly understandable. This is quite a feat … An important feature of Fiske’s model is the inclusion of the constructs musical interpretation and musical expression in addition to the traditional variables of pitch and rhythm. He argues that vectors for musical interpretation and musical expression as well as tonal and rhythmic vectors are critical to predictive music models. The argument addresses the issue of music listeners’ perceptions of consecutive musical patterns (phrases) as either different patterns, or a second pattern as derived from (similar to) the preceding pattern, or the same as the preceding pattern. These decisions are believed to be critical to music cognition. The goal is not to build a model of actual musical brain functioning, but rather to model musical cognitive behavior. The book accomplishes this goal brilliantly. It is a wonderful example of how important theory is to research in general, and specifically to music research.” – Dr. Jack Heller, Professor Emeritus, School of Music, University of South Florida
“This book constitutes a truly remarkable achievement. Not only is it, in one sense, a cogent and convincing distillation of the author’s lifelong research into music perception and cognition, but to continue the analogy from viniculture, it also provides a mature and deeply satisfying encounter with neural networks applied to musical thinking which lingers long in the mind after the initial reading. Fiske produces quite the most sophisticated argument in music cognition literature. The journey embarked upon in reading this text uses advanced calculus as a main vehicle for developing a vector analysis model of brain functioning, which not just mimics the human brain as it interprets and appreciates music, but actually learns to act like a human brain. At first, such a notion seems absurd, as Fiske himself comments. But as one follows Fiske’s sensitive and musically focussed arguments the potential for absurdity disappears. And this is the strength of this important book. Fiske takes the reader carefully, and with great attention to detail, first through the evolution of his own conversion to using artificial intelligence as a means to further our understanding of how music cognition works … This text is a compulsory one for all those interested in simulating how the brain actually processes musical stimuli in order that we might make the complex judgements about music in all its manifestations and practices across the globe.” – Robert Walker BMus (Hons), Ph.D., A.R.C.M., A.R.C.O., F.LC.M., Professor, School of Music and Music Education, University of New South Wales, Australia
Table of Contents
1. Introduction: Towards a cognitive model of musical listening
2. A concept model of musical thinking
3. A supervised model of musical learning
4. Musical interpretation and expression
5. Musical reasoning
6. Is music cognition limited to three decision-types?
7. Beyond neural networks