PDF | review of David Temperley’s “Music and Probability”. Cambridge, Massachusetts: MIT Press, , ISBN (hardcover) $ Music and probability / David Temperley. p. cm. Includes bibliographical references and index. Contents: Probabilistic foundations and background— Melody I. So, David Temperley is right to say, in the introduction to his new With Music and Probability, Temperley sets out to fulfill two main tasks: to give an introduction.
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The book is designed in a cumulative way, so it is best if it is read sequentially.
In particular they lead very naturally to ways of identifying the probability of actual note patterns. These issues are explored in chapter 5 with regard to monophonic ;robability and chapter 7 with regard to polyphonic music. This idea may sound strange to music theorists, eavid Temperley makes a convincing case for its application.
With regard to both meter and key, the models proposed are not merely models of information retrieval, but also shed light on other aspects of perception. He explains how probability is used to detect pitch or rhythm, and argues that in order to state that a certain composition is within a specific style we generate probabilities from different models, and assign the one with higher probability.
Style and Composition 9. Highly recommended for all who have an interest in algorithmic composition. Use the program compare-na to compare your note-address list with the correct one. Expectancies generated by melodic intervals: In chapter 2 the author surveys all the probability theory needed for the following chapters. There was a problem filtering reviews right now.
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Statistical Learning of Melodic Patterns 9. All of these programs gen-add, compare-na, tally-na are available for download above. Amazon Rapids Fun stories for kids on the go. A very accessible text, that explores deeper theoretical concepts concerning the syntax of music.
The Note-Address System You can evaluate a metrical model using the note-address system in the following way. Read more Read less.
David Temperley – Columbia University Department of Music
The davic of probabilistic ideas to music has been pursued only sporadically over the past four decades, but the time is ripe, Temperley argues, for a reconsideration of how probabilities shape music perception and even music itself. After this introduction, the book presents relevant concepts as needed. Would you like to tell us about a lower price? They can also be generated by the Melisma meter-finding program.
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This model is then expanded to accommodate polyphonic music. Not-beat lists can be generated using the probabilistic meter program; see instructions at the top of the code. A well written text, exploring a multi-faceted approach to music-theoretical thinking. Cognition gives us a more or less realistic, accurate perspective of the existence and behavior of the outside world.
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Expectation and Error Detection 65 5. Recent advances in the application of probability theory to other domains of cognitive modeling, coupled with new evidence and theoretical insights about the working of the musical mind, have laid the groundwork for more fruitful investigations.
Temperley gives it a good try but if the reader is not rather familiar with music theory and some elementary notion of how science attempts to understand something by modeling it, I’m afraid the book will not be too satisfying. Explore the Home Gift Guide. The final three chapters of the book explore a range of further issues in music and probability. They found it very difficult to extract useful information, which would help them to better understand how humans perceive or generate music.
Exploring the application of Bayesian probabilistic modeling techniques to musical issues, including the perception of key and meter. Used in error detection tests. Temperley does not apply the Bayesian approach as just a mathematical instrument used to make predictions.
Hence, an interested reader even one without a background in probability will learn much about mathematics and the psychological modeling of music perception and creation. His model is then compared with experimental results of how humans detect key in polyphonic music so as to show the robustness and cognitive reality of the model. Customers who viewed this item also viewed. Probabilistic Foundations and Background 7 2.