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Author: David Meredith Publisher: Springer ISBN: 3319259318 Category : Computers Languages : en Pages : 483
Book Description
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.
Author: David Meredith Publisher: Springer ISBN: 3319259318 Category : Computers Languages : en Pages : 483
Book Description
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.
Author: Soubhik Chakraborty Publisher: Springer ISBN: 3319114727 Category : Computers Languages : en Pages : 116
Book Description
The book opens with a short introduction to Indian music, in particular classical Hindustani music, followed by a chapter on the role of statistics in computational musicology. The authors then show how to analyze musical structure using Rubato, the music software package for statistical analysis, in particular addressing modeling, melodic similarity and lengths, and entropy analysis; they then show how to analyze musical performance. Finally, they explain how the concept of seminatural composition can help a music composer to obtain the opening line of a raga-based song using Monte Carlo simulation. The book will be of interest to musicians and musicologists, particularly those engaged with Indian music.
Author: Claus Weihs Publisher: CRC Press ISBN: 1498719570 Category : Business & Economics Languages : en Pages : 694
Book Description
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.
Author: Anikó Ekárt Publisher: Springer ISBN: 3030166678 Category : Computers Languages : en Pages : 261
Book Description
This book constitutes the refereed proceedings of the 8th International Conference on Evolutionary Computation in Combinatorial Optimization, EvoMUSART 2019, held in Leipzig, Germany, in April 2019, co-located with the Evo*2019 events EuroGP, EvoCOP and EvoApplications. The 16 revised full papers presented were carefully reviewed and selected from 24 submissions. The papers cover a wide range of topics and application areas, including: visual art and music generation, analysis, and interpretation; sound synthesis; architecture; video; poetry; design; and other creative tasks.
Author: Craig Stuart Sapp Publisher: Stanford University ISBN: Category : Languages : en Pages : 157
Book Description
Music is an art form which is realized in time. This dissertation presents computational methods for examining the temporality of music at multiple time-scales so that both short-term surface features and deeper long-term structures can be studied and related to each other. The methods are applied in particular to musical key analysis (Chapters 2-4) and also adapted for use in performance analysis (Chapters 5-6). The essential methodology is to examine all sequential time-scales within a piece using some analytic process and then arrange a summary of the analytic results into a maximally overlapped arrangement. Chapter 2 defines a two-dimensional plotting domain for displaying musical features at all possible time-scales which forms a basis for further analysis methods. The resulting structures in the plots can be examined subjectively as a navigational aid in the music as illustrated in Chapters 3 and 5. They can also be used to extract musically relevant information as discussed in Chapters 4 and 6.
Author: Guerino Mazzola Publisher: Springer Science & Business Media ISBN: 3642118380 Category : Computers Languages : en Pages : 285
Book Description
This book is a first sketch of what the overall field of performance could look like as a modern scientific field but not its stylistically differentiated practice, pedagogy, and history. Musical performance is the most complex field of music. It comprises the study of a composition’s expression in terms of analysis, emotion, and gesture, and then its transformation into embodied reality, turning formulaic facts into dramatic movements of human cognition. Combining these components in a creative way is a sophisticated mix of knowledge and mastery, which more resembles the cooking of a delicate recipe than a rational procedure. This book is the first one aiming at such comprehensive coverage of the topic, and it does so also as a university text book. We include musicological and philosophical aspects as well as empirical performance research. Presenting analytical tools and case studies turns this project into a demanding enterprise in construction and experimental setups of performances, especially those generated by the music software Rubato. We are happy that this book was written following a course for performance students at the School of Music of the University of Minnesota. Their education should not be restricted to the canonical practice. They must know the rationale for their performance. It is not sufficient to learn performance with the old-fashioned imitation model of the teacher's antetype, this cannot be an exclusive tool since it dramatically lacks the poetical precision asked for by Adorno's and Benjamin's micrologic. Without such alternatives to intuitive imitation, performance risks being disconnected from the audience.
Author: Emmanuel Amiot Publisher: Springer ISBN: 3319455818 Category : Computers Languages : en Pages : 214
Book Description
This book explains the state of the art in the use of the discrete Fourier transform (DFT) of musical structures such as rhythms or scales. In particular the author explains the DFT of pitch-class distributions, homometry and the phase retrieval problem, nil Fourier coefficients and tilings, saliency, extrapolation to the continuous Fourier transform and continuous spaces, and the meaning of the phases of Fourier coefficients. This is the first textbook dedicated to this subject, and with supporting examples and exercises this is suitable for researchers and advanced undergraduate and graduate students of music, computer science and engineering. The author has made online supplementary material available, and the book is also suitable for practitioners who want to learn about techniques for understanding musical notions and who want to gain musical insights into mathematical problems.
Author: David Cope Publisher: A-R Editions, Inc. ISBN: 0895796406 Category : Music Languages : en Pages : 376
Book Description
Today's computers provide music theorists with unprecedented opportunities to analyze music more quickly and accurately than ever before. Where analysis once required several weeks or even months to complete¿often replete with human errors, computers now provide the means to accomplish these same analyses in a fraction of the time and with far more accuracy. However, while such computer music analyses represent significant improvements in the field, computational analyses using traditional approaches by themselves do not constitute the true innovations in music theory that computers offer. In Hidden Structure: Music Analysis Using Computers David Cope introduces a series of analytical processes that¿by virtue of their concept and design¿can be better, and in some cases, only accomplished by computer programs, thereby presenting unique opportunities for music theorists to understand more thoroughly the various kinds of music they study.Following the introductory chapter that covers several important premises, Hidden Structure focuses on several unique approaches to music analysis offered by computer programs. While these unique approaches do not represent an all-encompassing and integrated global theory of music analysis, they do represent significantly more than a compilation of loosely related computer program descriptions. For example, Chapter 5 on function in post-tonal music, firmly depends on the scalar foundations presented in chapter 4. Likewise, chapter 7 presents a multi-tiered approach to musical analysis that builds on the material found in all of the preceding chapters. In short, Hidden Structure uniquely offers an integrated view of computer music analysis for today¿s musicians.
Author: Jean-Pierre Briot Publisher: Springer ISBN: 3319701630 Category : Computers Languages : en Pages : 303
Book Description
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.
Author: Lawrence Beaumont Shuster Publisher: Routledge ISBN: 1000535509 Category : Music Languages : en Pages : 356
Book Description
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.
Author: David Meredith
Author: David Meredith
Author: Soubhik Chakraborty
Author: Claus Weihs
Author: Anikó Ekárt
Author: Craig Stuart Sapp
Author: Guerino Mazzola
Author: Emmanuel Amiot
Author: David Cope
Author: Jean-Pierre Briot
Author: Lawrence Beaumont Shuster