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This book is a survey and analysis of how deep learning can be used to generate musical content. The authors offer a comprehensive presentation of the foundations of deep learning techniques for music generation. They also develop a conceptual framework used to classify and analyze various types of architecture, encoding models, generation strategies, and ways to control the generation. The five dimensions of this framework are: objective (the kind of musical content to be generated, e.g., melody, accompaniment); representation (the musical elements to be considered and how to encode them, e.g., chord, silence, piano roll, one-hot encoding); architecture (the structure organizing neurons, their connexions, and the flow of their activations, e.g., feedforward, recurrent, variational autoencoder); challenge (the desired properties and issues, e.g., variability, incrementality, adaptability); and strategy (the way to model and control the process of generation, e.g., single-step feedforward, iterative feedforward, decoder feedforward, sampling). To illustrate the possible design decisions and to allow comparison and correlation analysis they analyze and classify more than 40 systems, and they discuss important open challenges such as interactivity, originality, and structure. The authors have extensive knowledge and experience in all related research, technical, performance, and business aspects. The book is suitable for students, practitioners, and researchers in the artificial intelligence, machine learning, and music creation domains. The reader does not require any prior knowledge about artificial neural networks, deep learning, or computer music. The text is fully supported with a comprehensive table of acronyms, bibliography, glossary, and index, and supplementary material is available from the authors' website.
A presentation of music and language within an integrative, embodied perspective of brain mechanisms for action, emotion, and social coordination. This book explores the relationships between language, music, and the brain by pursuing four key themes and the crosstalk among them: song and dance as a bridge between music and language; multiple levels of structure from brain to behavior to culture; the semantics of internal and external worlds and the role of emotion; and the evolution and development of language. The book offers specially commissioned expositions of current research accessible both to experts across disciplines and to non-experts. These chapters provide the background for reports by groups of specialists that chart current controversies and future directions of research on each theme. The book looks beyond mere auditory experience, probing the embodiment that links speech to gesture and music to dance. The study of the brains of monkeys and songbirds illuminates hypotheses on the evolution of brain mechanisms that support music and language, while the study of infants calibrates the developmental timetable of their capacities. The result is a unique book that will interest any reader seeking to learn more about language or music and will appeal especially to readers intrigued by the relationships of language and music with each other and with the brain. Contributors Francisco Aboitiz, Michael A. Arbib, Annabel J. Cohen, Ian Cross, Peter Ford Dominey, W. Tecumseh Fitch, Leonardo Fogassi, Jonathan Fritz, Thomas Fritz, Peter Hagoort, John Halle, Henkjan Honing, Atsushi Iriki, Petr Janata, Erich Jarvis, Stefan Koelsch, Gina Kuperberg, D. Robert Ladd, Fred Lerdahl, Stephen C. Levinson, Jerome Lewis, Katja Liebal, Jônatas Manzolli, Bjorn Merker, Lawrence M. Parsons, Aniruddh D. Patel, Isabelle Peretz, David Poeppel, Josef P. Rauschecker, Nikki Rickard, Klaus Scherer, Gottfried Schlaug, Uwe Seifert, Mark Steedman, Dietrich Stout, Francesca Stregapede, Sharon Thompson-Schill, Laurel Trainor, Sandra E. Trehub, Paul Verschure
Providing a complete review of existing work in music emotion developed in psychology and engineering, Music Emotion Recognition explains how to account for the subjective nature of emotion perception in the development of automatic music emotion recognition (MER) systems. Among the first publications dedicated to automatic MER, it begins with
Pendragon Press is proud to offer this new, revised, and expanded edition of Formalized Music, Iannis Xenakis's landmark book of 1971. In addition to three totally new chapters examining recent breakthroughs in music theory, two original computer programs illustrating the actual realization of newly proposed methods of composition, and an appendix of the very latest developments of stochastic synthesis as an invitation to future exploration, Xenakis offers a very critical self-examination of his theoretical propositions and artistic output of the past thirty-five years. This edition of Formalized Music is an essential tool for understanding the man and the thought processes of one of this century's most important and revolutionary musical figures.
Spanning a millennium of musical history, this monumental volume brings together nearly forty leading authorities to survey the music of Western Europe in the Middle Ages. All of the major aspects of medieval music are considered, making use of the latest research and thinking to discuss everything from the earliest genres of chant, through the music of the liturgy, to the riches of the vernacular song of the trouvères and troubadours. Alongside this account of the core repertory of monophony, The Cambridge History of Medieval Music tells the story of the birth of polyphonic music, and studies the genres of organum, conductus, motet and polyphonic song. Key composers of the period are introduced, such as Leoninus, Perotinus, Adam de la Halle, Philippe de Vitry and Guillaume de Machaut, and other chapters examine topics ranging from musical theory and performance to institutions, culture and collections.
The book can be viewed as representing the birth of evolutionary biomusicology. What biological and cognitive forces have shaped humankind's musical behavior and the rich global repertoire of musical structures? What is music for, and why does every human culture have it? What are the universal features of music and musical behavior across cultures? In this groundbreaking book, musicologists, biologists, anthropologists, archaeologists, psychologists, neuroscientists, ethologists, and linguists come together for the first time to examine these and related issues. The book can be viewed as representing the birth of evolutionary biomusicology—the study of which will contribute greatly to our understanding of the evolutionary precursors of human music, the evolution of the hominid vocal tract, localization of brain function, the structure of acoustic-communication signals, symbolic gesture, emotional manipulation through sound, self-expression, creativity, the human affinity for the spiritual, and the human attachment to music itself. Contributors Simha Arom, Derek Bickerton, Steven Brown, Ellen Dissanayake, Dean Falk, David W. Frayer, Walter Freeman, Thomas Geissmann, Marc D. Hauser, Michel Imberty, Harry Jerison, Drago Kunej, François-Bernard Mâche, Peter Marler, Björn Merker, Geoffrey Miller, Jean Molino, Bruno Nettl, Chris Nicolay, Katharine Payne, Bruce Richman, Peter J.B. Slater, Peter Todd, Sandra Trehub, Ivan Turk, Maria Ujhelyi, Nils L. Wallin, Carol Whaling
How do we know music? We perform it, we compose it, we sing it in the shower, we cook, sleep and dance to it. Eventually we think and write about it. This book represents the culmination of such shared processes. Each of these essays, written by leading writers on popular music, is analytical in some sense, but none of them treats analysis as an end in itself. The books presents a wide range of genres (rock, dance, TV soundtracks, country, pop, soul, easy listening, Turkish Arabesk) and deals with issues as broad as methodology, modernism, postmodernism, Marxism and communication. It aims to encourage listeners to think more seriously about the 'social' consequences of the music they spend time with and is the first collection of such essays to incorporate contextualisation in this way.
A free ebook version of this title is available through Luminos, University of California Press’s Open Access publishing program for monographs. Visit www.luminosoa.org to learn more. How do keyboards make music playable? Drawing on theories of media, systems, and cultural techniques, Keys to Play spans Greek myth and contemporary Japanese digital games to chart a genealogy of musical play and its animation via improvisation, performance, and recreation. As a paradigmatic digital interface, the keyboard forms a field of play on which the book’s diverse objects of inquiry—from clavichords to PCs and eighteenth-century musical dice games to the latest rhythm-action titles—enter into analogical relations. Remapping the keyboard’s topography by way of Mozart and Super Mario, who head an expansive cast of historical and virtual actors, Keys to Play invites readers to unlock ludic dimensions of music that are at once old and new.
When Speech and Audio Signal Processing published in 1999, it stood out from its competition in its breadth of coverage and its accessible, intutiont-based style. This book was aimed at individual students and engineers excited about the broad span of audio processing and curious to understand the available techniques. Since then, with the advent of the iPod in 2001, the field of digital audio and music has exploded, leading to a much greater interest in the technical aspects of audio processing. This Second Edition will update and revise the original book to augment it with new material describing both the enabling technologies of digital music distribution (most significantly the MP3) and a range of exciting new research areas in automatic music content processing (such as automatic transcription, music similarity, etc.) that have emerged in the past five years, driven by the digital music revolution. New chapter topics include: Psychoacoustic Audio Coding, describing MP3 and related audio coding schemes based on psychoacoustic masking of quantization noise Music Transcription, including automatically deriving notes, beats, and chords from music signals. Music Information Retrieval, primarily focusing on audio-based genre classification, artist/style identification, and similarity estimation. Audio Source Separation, including multi-microphone beamforming, blind source separation, and the perception-inspired techniques usually referred to as Computational Auditory Scene Analysis (CASA).
This indispensable volume, a comprehensive and wide-ranging resource on Edward Said's life and work, spans his broad legacy both within and beyond the academy. The book brings together contributions from 31 luminaries to engage Said's provocative ideas.