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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MTO Casacuberta, Review of Music and Probability
Use the program tally-na if desired to take a series of outputs from compare-na and combine them. Music and the Psychology of Expectation.
The title of this book is somewhat misleading. 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.
Review As he did in The Cognition of Basic Musical StructuresTemperley here challenges the frontiers of the definition of music theory and cognition. Communicative Pressure Amazon Rapids Fun stories for kids on the go.
Probabilistic Foundations and Background 7 2.
Ships from and sold by Amazon. Buy the selected items together This item: They found it very difficult to extract useful information, which would help them to better understand how humans perceive or generate music.
Chapter eight surveys some recent work by other authors in which probabilistic methods are applied to a variety of problems in music perception and cognition: For example, they could recognize faces and speech, and they could play davic better than humans.
In chapter three the author addresses a basic problem of music perception – the identification meter – and proposes a probabilistic model of this process. This document and all portions thereof are protected by U. The scholarship is sound and the research original. As mentioned above, chapter 2 is a basic introduction to conditional probability, and other mathematical concepts are presented and explained when needed.
Items appearing in MTO may tsmperley saved and stored in electronic or paper form, and may be shared among individuals for purposes of scholarly research or discussion, but may not be republished in any form, electronic or print, without prior, written permission from the author sand advance notification of the editors of MTO.
Chapters 4 and 6 examine the problem of key perception from a probabilistic standpoint. Customers who bought this item also bought.
Music and Probability
See all 4 reviews. This in turn provides a way of modeling cognitive processes such as error detection, expectation, and pitch identification, as well as more subtle musical phenomena such probabolity musical ambiguity, tension, and “tonalness”. University of Chicago Press. Expectation and Error Detection 65 5.
This is a general problem that most probabilistic and neural networks models share, as stated in Clark But from there, you step off the deep end as he tries to explain the various models used for music perception such as how the perceiver comes to detect the particular rhythm or key of a piece of music.
Used in error detection tests. Please try again later. The final three chapters of the book explore a range of further issues in music and probability. Bayesian techniques also provide insights into such subtle and tmperley issues as musical ambiguity, tension, and “grammaticality,” and lead to interesting and novel predictions about compositional practice and differences between musical styles.
The following is pronability table of contents: 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.
David Temperley – Columbia University Department of Music
Several other notefiles used for other tests of the polyphonic key program: Prepared by Sean Atkinson, Editorial Assistant. The application 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.
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. Producers of communication are sensitive to, and affected by, its probabilistic nature. Temperley needed to rethink carefully how to present some rather esoteric models in a way that would be accessible to the average intelligent reader.
Try the Kindle edition and experience these great reading features: Temperley proposes computational models for two basic cognitive processes, the perception of key and the perception of meter, using daviid of Bayesian probabilistic modeling.
If flags can be used, they are placed after the program name, possibly with a number after them: Temperley does not apply the Bayesian approach as just a mathematical instrument used to nad predictions.