Machine Models of Music [Hardcover]

Stephan Schwanauer (Author), David Levitt (Author)

Book Description

Publication Date: January 8, 1993

Machine Models of Music brings together representative models ranging from Mozart's "Musical Dice Game" to a classic article by Marvin Minsky and current research to illustrate the rich impact that artificial intelligence has had on the understanding and composition of traditional music and to demonstrate the ways in which music can push the boundaries of traditional Al research.Major sections of the book take up pioneering research in generate-and-test composition (Lejaren Hiller, Barry Brooks, Jr., Stanley Gill); composition parsing (Allen Forte, Herbert Simon, Terry Winograd); heuristic composition (John Rothgeb, James Moorer, Steven Smoliar); generative grammars (Otto Laske, Gary Rader, Johan Sundberg, Fred Lerdahl); alternative theories (Marvin Minsky, James Meehan); composition tools (Charles Ames, Kemal Ebcioglu, David Cope, C. Fry); and new directions (David Levitt, Christopher Longuet-Higgins, Jamshed Bharucha, Stephan Schwanauer).Stephan Schwanauer is President of Mediasoft Corporation. David Levitt is the founder of HIP Software and head of audio products at VPL Research.

Editorial Reviews

About the Author

David Levitt is the founder of HIP Software and head of audio products at VPL Research.

Stephan Schwanauer is President of Mediasoft Corporation.

Product Details

• Hardcover: 556 pages
• Publisher: The MIT Press (January 8, 1993)
• Language: English
• ISBN-10: 0262193191
• ISBN-13: 978-0262193191
• Product Dimensions: 9.1 x 6.2 x 1.4 inches
• Shipping Weight: 2.2 pounds (View shipping rates and policies)
• Average Customer Review: 5.0 out of 5 stars  See all reviews (1 customer review)
• Amazon Best Sellers Rank: #2,603,087 in Books (See Top 100 in Books)

Customer Reviews

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2 of 2 people found the following review helpful:

5.0 out of 5 stars Harmonizing the Art of Music With the Science of Music, February 20, 2006

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Ralph White (New England) - See all my reviews
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This review is from: Machine Models of Music (Hardcover)

The editors' premise in assembling these twenty-three essays is that since it is possible to model human thought, particularly advanced logic and artificial intelligence, then it should also be possible to model creative thought, and in particular, musically creative thought. Machine Models of Music is not entirely about getting machines to be creative; it is also about understanding the human mind by modeling its approximate behavior algorithmically. Much of it is very technical, e.g., author Charles Ames discovery that "algorithmic methods of composition could be much more powerful than had previously been demonstrated..." as published in the 1981 International Computer Music Conference. We are also treated to somewhat more accessible papers, such as James Anderson Moorer's article, "Music and Computer Composition" which views music modeling and speech modeling as closely-related disciplines. For a fun challenge, see the "Musical Dice Game" written by Wolfgang Amadeus Mozart, which shows how to compose waltzes with two dice. I took particular interest in the editor's own paper, "A Learning Machine for Tonal Composition," by Stephan Schwanauer. Schwanauer (aka, "The Count of Palo Alto") developed The Music Understanding System Evolver (MUSE) as his Ph.D. thesis at Yale in 1986 with the cooperation of Yale's Music and Computer Science Departments.

At its writing, this book was a pioneering effort in harmonizing the art of music with the science of music. In the process it took a giant step toward its fundamental objective of understanding the mechanics of human thought.