This book provides an in-depth introduction and overview of current research in computational music analysis. Its seventeen chapters, written by leading researchers, collectively represent the diversity as well as the technical and philosophical sophistication of the work being done today in this intensely interdisciplinary field. A broad range of approaches are presented, employing techniques originating in disciplines such as linguistics, information theory, information retrieval, pattern recognition, machine learning, topology, algebra and signal processing. Many of the methods described draw on well-established theories in music theory and analysis, such as Forte's pitch-class set theory, Schenkerian analysis, the methods of semiotic analysis developed by Ruwet and Nattiez, and Lerdahl and Jackendoff's Generative Theory of Tonal Music. The book is divided into six parts, covering methodological issues, harmonic and pitch-class set analysis, form and voice-separation, grammars and hierarchical reduction, motivic analysis and pattern discovery and, finally, classification and the discovery of distinctive patterns. As a detailed and up-to-date picture of current research in computational music analysis, the book provides an invaluable resource for researchers, teachers and students in music theory and analysis, computer science, music information retrieval and related disciplines. It also provides a state-of-the-art reference for practitioners in the music technology industry.

This book introduces a theory of music analysis that one can use to explore aspects of segmentation and associative organization in a wide range of repertoire including Western classical music from the Baroque to the present, with potential applications to jazz and popular music, and some non-Western musics. Rather than a methodology, the theory provides analysts with precise language and a broad, flexible conceptual framework through which they can formulate and investigate questions of interest and develop their own interpretations of individual pieces and passages. The theory begins with a basic distinction among three domains of musical experience and discourse about it: the sonic (psychoacoustic); the contextual (or associative, sparked by varying degrees of repetition); and the structural (guided by a specific theory of musical structure or syntax invoked by the analyst). A comprehensive presentation of the theory, with copious musical illustrations, is balanced with close analyses of works by Beethoven, Debussy, Nancarrow, Riley, Feldman, and Morris. Dora A. Hanninen is professor of music theory at the University of Maryland. She received the 2010 Outstanding Publication Award from the Society for Music Theory.

This volume brings together a group of analytical chapters exploring traditional genres and styles of world music, capturing a vibrant and expanding field of research. These contributors, drawn from the forefront of researchers in world music analysis, seek to break down barriers and build bridges between scholarly disciplines, musical repertoires, and cultural traditions. Covering a wide range of genres, styles, and performers, the chapters bring to bear a variety of methodologies, including indigenous theoretical perspectives, Western music theory, and interdisciplinary techniques rooted in the cognitive and computational sciences. With contributors addressing music traditions from Africa, Asia, Europe, and the Americas, this volume captures the many current directions in the analysis of world music, offering a state of the fi eld and demonstrating the expansion of possibilities created by this area of research.

(Guitar Educational). Experience must-know music knowledge and wisdom through the highly focused lens of legendary guitar virtuoso Steve Vai. This full-color instructional book written by Vai himself features in-depth discussions of the music theory fundamentals that every aspiring (and veteran) guitar player should know, packed with practical exercises, diagrams, tips, inspiring ideas and concepts, practice methods, and ways of looking at music that you may have never considered. Topics covered include: academic vs. experiential learning * reading and writing music * key signatures * chord scales * rhythm basics * guitar harmonics * modes * and much more.

This book provides a comprehensive overview of music data analysis, from introductory material to advanced concepts. It covers various applications including transcription and segmentation as well as chord and harmony, instrument and tempo recognition. It also discusses the implementation aspects of music data analysis such as architecture, user interface and hardware. It is ideal for use in university classes with an interest in music data analysis. It also could be used in computer science and statistics as well as musicology.