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Connectionist Models Of Musical Thinking (Studies in the History & Interpretation of Music)

Harold E. Fiske

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Description:This book describes a series of neural network models devised to represent music listening processes. Backpropagation, Adaptive Resonance Theory, and other connectionist procedures are used to model melodic perception, interpretation, and expression. Preface; 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. In Chapter 1, Fiske provides a comprehensive review of the pros and cons of connectionist or neural network modeling, including support for the idea of the parallel processing of rhythm and pitch information from his own chronometric (or reaction-time) perceptual experiments. Central to this whole exposition are the similarities and differences between computer and biological neural networks, and the debate as to whether connectionist models reproduce neural activities, or whether they represent cognitive processing on a more metaphorical level. Historically, this has been a complex debate with passionate and eloquent adherents on both sides. Fiske notes, however, that, at the very least, a properly functioning neural network model supports the internal logic of the theory that initiated it. Moreover, if the neural net approximates human behavior, then its theory provides one plausible explanation of that behavior, thus bolstering the external validity of the theory. Therefore the prerequisites for maximizing both the internal and external validity of a theory are (1) a solid theory, (2) a well-designed connectionist model and (3) carefully collected human-response data. With these principles in mind, in the ensuing chapters, Fiske leads the reader on a carefully conducted tour of his theory and the neural-net models derived from it. Chapter 2 revisits Fiske's cognitive theory of hierarchical decision making and (re)presents it as an operationalized conceptual model. The basic mechanics of a connectionist model are explained, including the defining of musical pitch information as a vector. Interestingly, the author also takes some time to address two objections to his theory: (a) that there are actually only two cognitive categories (same versus different) and (b) that there is an infinite array of possible cognitive categories. In addition to the arguments that Fiske presents at this juncture, there is also the evidence from writings on musical structure, admittedly circumstantial evidence perhaps, that suggest that Fiske's three categories accord with the intuitions of music theorists. I shall return to this issue at the end of this Foreword. Chapter 3 describes Fiske's supervised model. After further discussion of vectors, autoassociators and backpropagation, the construction of the connectionist model is portrayed in detail. The goal of this model is to compare two tonal-rhythmic patterns and assign them to one of Fiske's three categories (P, P', Pn). For each tonal-rhythmic pattern, separate vectors for pitch class, octave and rhythm are constructed, the differences between two patterns for each parameter are computed, and then the difference computations are synthesized. The overall difference vector is assigned to one of the three categories but the boundaries between categories overlap, reflecting the disagreement am...We have made it easy for you to find a PDF Ebooks without any digging. And by having access to our ebooks online or by storing it on your computer, you have convenient answers with Connectionist Models Of Musical Thinking (Studies in the History & Interpretation of Music). To get started finding Connectionist Models Of Musical Thinking (Studies in the History & Interpretation of Music), you are right to find our website which has a comprehensive collection of manuals listed.
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ISBN: 0773461922

Description: This book describes a series of neural network models devised to represent music listening processes. Backpropagation, Adaptive Resonance Theory, and other connectionist procedures are used to model melodic perception, interpretation, and expression. Preface; 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. In Chapter 1, Fiske provides a comprehensive review of the pros and cons of connectionist or neural network modeling, including support for the idea of the parallel processing of rhythm and pitch information from his own chronometric (or reaction-time) perceptual experiments. Central to this whole exposition are the similarities and differences between computer and biological neural networks, and the debate as to whether connectionist models reproduce neural activities, or whether they represent cognitive processing on a more metaphorical level. Historically, this has been a complex debate with passionate and eloquent adherents on both sides. Fiske notes, however, that, at the very least, a properly functioning neural network model supports the internal logic of the theory that initiated it. Moreover, if the neural net approximates human behavior, then its theory provides one plausible explanation of that behavior, thus bolstering the external validity of the theory. Therefore the prerequisites for maximizing both the internal and external validity of a theory are (1) a solid theory, (2) a well-designed connectionist model and (3) carefully collected human-response data. With these principles in mind, in the ensuing chapters, Fiske leads the reader on a carefully conducted tour of his theory and the neural-net models derived from it. Chapter 2 revisits Fiske's cognitive theory of hierarchical decision making and (re)presents it as an operationalized conceptual model. The basic mechanics of a connectionist model are explained, including the defining of musical pitch information as a vector. Interestingly, the author also takes some time to address two objections to his theory: (a) that there are actually only two cognitive categories (same versus different) and (b) that there is an infinite array of possible cognitive categories. In addition to the arguments that Fiske presents at this juncture, there is also the evidence from writings on musical structure, admittedly circumstantial evidence perhaps, that suggest that Fiske's three categories accord with the intuitions of music theorists. I shall return to this issue at the end of this Foreword. Chapter 3 describes Fiske's supervised model. After further discussion of vectors, autoassociators and backpropagation, the construction of the connectionist model is portrayed in detail. The goal of this model is to compare two tonal-rhythmic patterns and assign them to one of Fiske's three categories (P, P', Pn). For each tonal-rhythmic pattern, separate vectors for pitch class, octave and rhythm are constructed, the differences between two patterns for each parameter are computed, and then the difference computations are synthesized. The overall difference vector is assigned to one of the three categories but the boundaries between categories overlap, reflecting the disagreement am...We have made it easy for you to find a PDF Ebooks without any digging. And by having access to our ebooks online or by storing it on your computer, you have convenient answers with Connectionist Models Of Musical Thinking (Studies in the History & Interpretation of Music). To get started finding Connectionist Models Of Musical Thinking (Studies in the History & Interpretation of Music), you are right to find our website which has a comprehensive collection of manuals listed.
Our library is the biggest of these that have literally hundreds of thousands of different products represented.

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