This book is intended for researchers interested in using computational methods and tools to engage with music, dance and theatre. The chapters have evolved out of presentations and deliberations at an international workshop entitled Computer Assisted Music and Dramatics: Possibilities and Challenges organized by University of Mumbai in honour of Professor Hari Sahasrabuddhe, a renowned educator and a pioneering computational musicologist (CM) of Indian classical music. The workshop included contributions from CM as well as musicians with a special focus on South Asian arts. The case studies and reflective essays here are based on analyses of genres, practices and theoretical constructs modelled computationally. They offer a balanced and complementary perspective to help innovation in the synthesis of music by extracting information from recorded performances. This material would be of interest to scholars of the sciences and humanities and facilitate exchanges and generation of ideas.

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.

Pascal Programming for Music Research addresses those who wish to develop the programming skills necessary for doing computer-assisted music research, particularly in the fields of music theory and musicology. Many of the programming techniques are also applicable to computer assisted instruction (CAI), composition, and music synthesis. The programs and techniques can be implemented on personal computers or larger computer systems using standard Pascal compilers and will be valuable to anyone in the humanities creating data bases. Among its useful features are: -complete programs, from simple illustrations to substantial applications; -beginning programming through such advanced topics as linked data structures, recursive algorithms, DARMS translation, score processing; -bibliographic references at the end of each chapter to pertinent sources in music theory, computer science, and computer applications in music; -exercises which explore and extend topics discussed in the text; -appendices which include a DARMS translator and a library of procedures for building and manipulating a linked representation of scores; -most algorithms and techniques that are given in Pascal programming translate easily to other computer languages. Beginning, as well as advanced, programmers and anyone interested in programming music applications will find this book to be an invaluable resource.

Providing a distillation of knowledge in the various disciplines of arts education (dance, drama, music, literature and poetry and visual arts), this essential handbook synthesizes existing research literature, reflects on the past, and contributes to shaping the future of the respective and integrated disciplines of arts education. While research can at times seem distant from practice, the Handbook aims to maintain connection with the live practice of art and of education, capturing the vibrancy and best thinking in the field of theory and practice. The Handbook is organized into 13 sections, each focusing on a major area or issue in arts education research.

This book features research papers presented at the International Conference on Emerging Technologies in Data Mining and Information Security (IEMIS 2020) held at the University of Engineering & Management, Kolkata, India, during July 2020. The book is organized in three volumes and includes high-quality research work by academicians and industrial experts in the field of computing and communication, including full-length papers, research-in-progress papers and case studies related to all the areas of data mining, machine learning, Internet of things (IoT) and information security.

In Knowledge-Based Programming for Music Research, Schaffer and McGee explore expert systems for applications in artificial intelligence (AI). The text concerns (1) basic principles for knowledge-based programming, (2) concepts and strategies for programming these systems, (3) a "universal data" model for music analysis, and (4) examples that concern specific aspects of design and application. The authors also investigate Prolog (programming in logic), one of the most widely used computer languages for AI, and base some of their applications on the recent implication-based theories of Eugene Narmour. Of the applications for programming a knowledge-based system, music analysis has the most potential. Beyond identifying isolated elements, it is possible to create programs that extend to chord structures and other, more complex structures. This kind of programming allows the authors to embed the rules of composition in the application and then extend the analysis throughout the musical work. It also allows them to arrive at the underlying principles for a given composition. As a tool for music analysis, such programming has profound implications for further growth. The text is designed for musicians at various levels and could also be used in courses on computer-music programming. Parts of the book have been successfully used in courses on computer programming for music research, with which the authors have direct experience. The text includes extensive examples of code for use in individual Prolog applications and a comprehensive bibliography.