As one of our highest expressions of thought and creativity, music has always been a difficult realm to capture, model, and understand. The connectionist paradigm, now beginning to provide insights into many realms of human behavior, offers a new and unified viewpoint from which to investigate the subtleties of musical experience. Music and Connectionism provides a fresh approach to both fields, using the techniques of connectionism and parallel distributed processing to look at a wide range of topics in music research, from pitch perception to chord fingering to composition.The contributors, leading researchers in both music psychology and neural networks, address the challenges and opportunities of musical applications of network models. The result is a current and thorough survey of the field that advances understanding of musical phenomena encompassing perception, cognition, composition, and performance, and in methods for network design and analysis.Peter M. Todd is a doctoral candidate in the PDP Research Group of the Psychology Department at Stanford University. Gareth Loy is an award-winning composer, a lecturer in the Music Department of the University of California, San Diego, and a member of the technical staff of Frox Inc.Contributors. Jamshed J. Bharucha. Peter Desain. Mark Dolson. Robert Gjerclingen. Henkjan Honing. B. Keith Jenkins. Jacqueline Jons. Douglas H. Keefe. Tuevo Kohonen. Bernice Laden. Pauli Laine. Otto Laske. Marc Leman. J. P. Lewis. Christoph Lischka. D. Gareth Loy. Ben Miller. Michael Mozer. Samir I. Sayegh. Hajime Sano. Todd Soukup. Don Scarborough. Kalev Tiits. Peter M. Todd. Kari Torkkola.
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Editorial Reviews
About the Author
Peter M. Todd is a professor of Cognitive Science, Informatics, and Psychology at Indiana University in Bloomington. His research focuses on the ways that people have evolved to make good decisions in a variety of environments. Gareth Loy is a musician and award-winning composer. He has published widely and, during a long and successful career at the cutting edge of multimedia computing, has worked as a researcher, lecturer, programmer, software architect, and digital systems engineer. He is President of Gareth, Inc., a provider of software engineering and consulting services internationally.
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5 of 6 people found the following review helpful:
5.0 out of 5 stars
A great book for using Neural Networks to compose music.,
By Uri <noony@sitcom.co.il> (Israel) - See all my reviews
This review is from: Music and Connectionism (Hardcover)
Neural Networks are becoming more and more popular these days, and it's interesting to learn one can use them to compose music. The authors of this book did this with some success. If you are interested in Neural Networks, and in computer composed music - this is the book for you. There are various articles by different authors on this subject. All the articles appeared in the computer music journal in 1989.
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First Sentence:
Most computer users have become so accustomed to the standard von Neumann approach to computing that they rarely question the fundamental assumptions implicit in the underlying architecture. Read the first page Key Phrases - Capitalized Phrases (CAPs): (learn more)
New York, Microstructure of Cognition, Technical Report, Pitch Class Cluster, Erlbaum Associates, Computer Music Association, Psychological Review, San Francisco, Machine Tongues, Morgan Kaufmann, San Diego, University of California, Massachusetts Institute of Technology, Journal of Experimental Psychology, Learning Internal Representations, References Bharucha, San Mateo, Academic Press, Menlo Park, Neural Information Processing Systems, Priming of Chords, Stanford University, The Macmillan Press, International Conference, Tonal Hierarchies New!
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Front Cover | Front Flap | Table of Contents | First Pages | Back Flap | Back Cover | Surprise Me!
Most computer users have become so accustomed to the standard von Neumann approach to computing that they rarely question the fundamental assumptions implicit in the underlying architecture. Read the first page Key Phrases - Capitalized Phrases (CAPs): (learn more)
New York, Microstructure of Cognition, Technical Report, Pitch Class Cluster, Erlbaum Associates, Computer Music Association, Psychological Review, San Francisco, Machine Tongues, Morgan Kaufmann, San Diego, University of California, Massachusetts Institute of Technology, Journal of Experimental Psychology, Learning Internal Representations, References Bharucha, San Mateo, Academic Press, Menlo Park, Neural Information Processing Systems, Priming of Chords, Stanford University, The Macmillan Press, International Conference, Tonal Hierarchies New!
Concordance | Text Stats Browse Sample Pages:
Front Cover | Front Flap | Table of Contents | First Pages | Back Flap | Back Cover | Surprise Me!
Citations (learn more)
This book cites 46
books:
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16
books
cite this book:
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- Cognitive Science (Handbook of Perception and Cognition, Second Edition) by Benjamin Martin Bly on 9 pages
- Self-organization and associative memory (Springer series in information sciences) by Teuvo Kohonen on 5 pages
- Parallel Distributed Processing: Explorations in the Microstructure of Cognition: Foundations (Volume 1) by David E. Rumelhart on 5 pages
- Emotion and Meaning in Music (Phoenix Books) by Leonard B. Meyer on 4 pages
- Music Cognition (Academic Press Series in Cognition and Perception) by W. Jay Dowling on page 59, page 136, and page 146
See all 46 books this book cites
- Readings in Music and Artificial Intelligence (Contemporary Music Studies) by Eduardo Reck Miranda on page 65, page 66, and page 67
- Ways of Listening: An Ecological Approach to the Perception of Musical Meaning by Eric F. Clarke in Back Matter (1), Back Matter (2), and Back Matter (3)
- Perception-Based Data Processing in Acoustics: Applications to Music Information Retrieval and Psychophysiology of Hearing (Studies in Computational Intelligence) by Bozena Kostek on page 304, page 305, and page 311
- Time Series Prediction: Forecasting The Future And Understanding The Past (Santa Fe Institute Series) by Andreas S. Weigend in Back Matter (1), and Back Matter (2)
- Pitch: Neural Coding and Perception (Springer Handbook of Auditory Research) by Christopher J. Plack in Back Matter (1), and Back Matter (2)
See all 16 books citing this book
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