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This anthology provides an informative and timely introduction to ongoing research on music as a cognitive process, bringing a new coherence to the emerging science of musical activity. Following the foreword, which is based on a conversation with Marvin Minsky, 26 contributions explore musical composition, analysis, performance, perception, and learning and tutoring. Their goal is to discover how these activities can be interpreted, understood, modeled, and supported through the use of computer programs. Each chapter is put into perspective by the editors, and empirical investigations are framed by a discussion of the nature of cognitive musicology and of epistemological problems of modeling musical action. The contributions, drawn from two international workshops on AI and Music held in 1988 and 1989, are grouped in seven sections. Topics in these sections take up two views of the nature of cognitive musicology (Kugel, Laske), principles of modeling musical activity (Balaban, Bel, Blevis, Glasgow and Jenkins, Courtot, Smoliar), approaches to music composition (Ames and Domino, Laske, Marsella, Riecken), music analysis by synthesis (Cope, Ebcioglu, Maxwell), realtime performance of music (Bel and Kippen, Ohteru and Hashimoto), music perception (Desain and Honing, Jones, Miller and Scarborough, Linster), and learning/tutoring (Baker, Widmer).
The interplay between emotional and intellectual elements feature heavily in the research of a variety of scientific fields, including neuroscience, the cognitive sciences and artificial intelligence (AI). This collection of key introductory texts by top researchers worldwide is the first study which introduces the subject of artificial intelligence and music to beginners. Eduardo Reck Miranda received a Ph.D. in music and artificial intelligence from the University of Edinburgh, Scotland. He has published several research papers in major international journals and his compositions have been performed worldwide. Also includes 57 musical examples.
Master musical skills quickly and easily! From classical music to new age, hard rock, and pop, music has always played an important role in everyday life. Whether you're an intermediate musician or an aspiring music major, The Everything Essential Music Theory Book is a guide to mastering one of the most important tools for every musician: musical understanding. This compact, portable volume covers all the basics, including: The construction of chords and scales How to understand rhythm and time signatures How keys are identified and organized Creating harmonization and melody With each clear and easy-to-understand chapter, musician and educator Marc Schonbrun takes you through the essentials of music theory--the very glue that holds music together.
Unique, Simple and Straightforward Way to Learn Music Theory and Become a Better Musician, Even if You're a Total Beginner! * Updated and massively Expanded edition with Audio examples, new Exercises, and over 150 pages of NEW content! * ** On a special promo price for a limited time! ** Have you ever wanted: To know how understanding music theory can make you a better player (on any instrument)? To unlock the mysteries of notes, intervals, music scales, modes, keys, circle of fifths, chords and chord progressions, and other important concepts in music, and how they all relate to one another? To get a deep understanding of scales, modes and chords, where they come from, what are the different types that exist, how they're built, and how to use any chord or scale in your playing? To learn how rhythm works and how to master your rhythm and time skills that will make you sound like a pro? To know what's the magic behind all the beautiful music that you love and how you can (re)create it? To get a broad perspective of tonal harmony, and how melody, harmony, and rhythm work together? Understand advanced concepts (such as modal playing, atonality, polytonality, free music, etc.) that usually only advanced jazz musicians use? But... Have you ever been put off by music theory or thought that it wasn't necessary, boring or too hard to learn? If you find yourself in any of this, then this book is what you need. It covers pretty much everything that anyone who plays or wants to play music, and wishes to become a better musician, should know. This is one of the most comprehensive and straightforward, evergreen books on music theory that you can find, and you will wish to study it often and keep it forever. The book is structured in a way that is very easy to follow and internalize all the concepts that are explained. You don't have to be a college degree music student in order to understand and use any of this - anyone can do it, even a total beginner! It also doesn't matter what instrument(s) you play nor what is your level of knowledge or playing ability, because music theory is universal and all about what sounds good together! It explains the WHY and HOW, and it is your roadmap, a skill and a tool - guided by your ears - for creating beautiful music This book will give you what is necessary to become a true expert in music theory without frustration and feeling overwhelmed in the process, and this in-turn will have immense benefits to your playing and musicianship! Just use the look inside feature by clicking on the book cover to get a sneak peak of what you'll learn inside... Get this book now and solve all your problems with music theory, and become proficient in this field! Pick up your copy by clicking on the BUY now button at the top of this page.
Build a solid foundation in surgical AI with this engaging, comprehensive guide for AI novices Machine learning, neural networks, and computer vision in surgical education, practice, and research will soon be de rigueur. Written for surgeons without a background in math or computer science, Artificial Intelligence in Surgery provides everything you need to evaluate new technologies and make the right decisions about bringing AI into your practice. Comprehensive and easy to understand, this first-of-its-kind resource illustrates the use of AI in surgery through real-life examples. It covers the issues most relevant to your practice, including: Neural Networks and Deep Learning Natural Language Processing Computer Vision Surgical Education and Simulation Preoperative Risk Stratification Intraoperative Video Analysis OR Black Box and Tracking of Intraoperative Events Artificial Intelligence and Robotic Surgery Natural Language Processing for Clinical Documentation Leveraging Artificial Intelligence in the EMR Ethical Implications of Artificial Intelligence in Surgery Artificial Intelligence and Health Policy Assessing Strengths and Weaknesses of Artificial Intelligence Research Finally, the appendix includes a detailed glossary of terms and important learning resources and techniques―all of which helps you interpret claims made by studies or companies using AI.
The psychological theory of expectation that David Huron proposes in Sweet Anticipation grew out of the author's experimental efforts to understand how music evokes emotions. These efforts evolved into a general theory of expectation that will prove informative to readers interested in cognitive science and evolutionary psychology as well as those interested in music. The book describes a set of psychological mechanisms and illustrates how these mechanisms work in the case of music. All examples of notated music can be heard on the Web. Huron proposes that emotions evoked by expectation involve five functionally distinct response systems: reaction responses (which engage defensive reflexes); tension responses (where uncertainty leads to stress); prediction responses (which reward accurate prediction); imagination responses (which facilitate deferred gratification); and appraisal responses (which occur after conscious thought is engaged). For real-world events, these five response systems typically produce a complex mixture of feelings. The book identifies some of the aesthetic possibilities afforded by expectation, and shows how common musical devices (such as syncopation, cadence, meter, tonality, and climax) exploit the psychological opportunities. The theory also provides new insights into the physiological psychology of awe, laughter, and spine-tingling chills. Huron traces the psychology of expectations from the patterns of the physical/cultural world through imperfectly learned heuristics used to predict that world to the phenomenal qualia we experienced as we apprehend the world.
A concise overview of machine learning—computer programs that learn from data—which underlies applications that include recommendation systems, face recognition, and driverless cars. Today, machine learning underlies a range of applications we use every day, from product recommendations to voice recognition—as well as some we don't yet use everyday, including driverless cars. It is the basis of the new approach in computing where we do not write programs but collect data; the idea is to learn the algorithms for the tasks automatically from data. As computing devices grow more ubiquitous, a larger part of our lives and work is recorded digitally, and as “Big Data” has gotten bigger, the theory of machine learning—the foundation of efforts to process that data into knowledge—has also advanced. In this book, machine learning expert Ethem Alpaydin offers a concise overview of the subject for the general reader, describing its evolution, explaining important learning algorithms, and presenting example applications. Alpaydin offers an account of how digital technology advanced from number-crunching mainframes to mobile devices, putting today's machine learning boom in context. He describes the basics of machine learning and some applications; the use of machine learning algorithms for pattern recognition; artificial neural networks inspired by the human brain; algorithms that learn associations between instances, with such applications as customer segmentation and learning recommendations; and reinforcement learning, when an autonomous agent learns act so as to maximize reward and minimize penalty. Alpaydin then considers some future directions for machine learning and the new field of “data science,” and discusses the ethical and legal implications for data privacy and security.
From the author of The Changing Mind and The Organized Mind comes a New York Times bestseller that unravels the mystery of our perennial love affair with music ***** 'What do the music of Bach, Depeche Mode and John Cage fundamentally have in common?' Music is an obsession at the heart of human nature, even more fundamental to our species than language. From Mozart to the Beatles, neuroscientist, psychologist and internationally-bestselling author Daniel Levitin reveals the role of music in human evolution, shows how our musical preferences begin to form even before we are born and explains why music can offer such an emotional experience. In This Is Your Brain On Music Levitin offers nothing less than a new way to understand music, and what it can teach us about ourselves. ***** 'Music seems to have an almost wilful, evasive quality, defying simple explanation, so that the more we find out, the more there is to know . . . Daniel Levitin's book is an eloquent and poetic exploration of this paradox' Sting 'You'll never hear music in the same way again' Classic FM magazine 'Music, Levitin argues, is not a decadent modern diversion but something of fundamental importance to the history of human development' Literary Review
This book constitutes the thoroughly refereed post-proceedings of the 7th International Symposium on Computer Music Modeling and Retrieval, CMMR 2010, held in Málaga, Spain, in June 2010. The 22 revised full papers presented were specially reviewed and revised for inclusion in this proceedings volume. The book is divided in five main chapters which reflect the present challenges within the field of computer music modeling and retrieval. The chapters range from music interaction, composition tools and sound source separation to data mining and music libraries. One chapter is also dedicated to perceptual and cognitive aspects that are currently subject to increased interest in the MIR community.