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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 offers 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 of methods for network design and analysis.

Music and Connectionism is based on a core of articles that originally appeared in two special issues of computer Music Journal. These are augmented with addenda covering more recent research by the authors. The book opens with tutorial chapters introducing neural networks in a musical context and relevant aspects of previous computer music research, making this a self-contained text. There are many new chapters,along with new section introductions, summaries of related work, and a debate on the artistic implications of connectionist methods.

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