The problems it addresses include emotion representation, annotation of music excerpts, feature extraction, and machine learning. The book chiefly focuses on content-based analysis of music files, a system that automatically analyzes the structures of a music file and annotates the file with the perceived emotions. Further, it explores emotion detection in MIDI and audio files. In the experiments presented here, the categorical and dimensional approaches were used, and the knowledge and expertise of music experts with a university music education were used for music file annotation. The automatic emotion detection systems constructed and described in the book make it possible to index and subsequently search through music databases according to emotion. In turn, the emotion maps of musical compositions provide valuable new insights into the distribution of emotions in music and can be used to compare that distribution in different compositions, or to conduct emotional comparisons of different interpretations of the same composition.

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

The unique compendium re-assesses the value of future and emergent computing technologies via artistic and philosophical means. The book encourages scientists to adopt inspiring thinking of artists and philosophers to reuse scientific concepts in their works.The useful reference text consists of non-typical topics, where artistic and philosophical concepts encourage readers to adopt unconventional approaches towards computing and immerse themselves into discoveries of future emerging landscape.Related Link(s)

This book constitutes the proceedings of the 25th International Symposium on Foundations of Intelligent Systems, ISMIS 2020, held in Graz, Austria, in October 2020. The conference was held virtually due to the COVID-19 pandemic. The 35 full and 8 short papers presented in this volume were carefully reviewed and selected from 79 submissions. Included is also one invited talk. The papers deal with topics such as natural language processing; deep learning and embeddings; digital signal processing; modelling and reasoning; and machine learning applications.

This book presents comprehensive coverage of the latest advances in research into enabling machines to listen to and compose new music. It includes chapters introducing what we know about human musical intelligence and on how this knowledge can be simulated with AI. The development of interactive musical robots and emerging new approaches to AI-based musical creativity are also introduced, including brain–computer music interfaces, bio-processors and quantum computing. Artificial Intelligence (AI) technology permeates the music industry, from management systems for recording studios to recommendation systems for online commercialization of music through the Internet. Yet whereas AI for online music distribution is well advanced, this book focuses on a largely unexplored application: AI for creating the actual musical content.

Interactive marketing, as one of the fastest growing academic fields in contemporary business world, is the multi-directional value creation and mutual-influence marketing process through active customer connection, engagement, participation and interaction. Contemporary interactive marketing has moved beyond the scope of direct marketing or digital marketing, as the market is becoming a forum for conversations and interactions among connected actors or participants in platform ecosystems. The advancement of mobile technology with interactive content and personalized experience makes interactive marketing the new normal in the business world. This handbook contains the most comprehensive and cutting-edge knowledge in the interactive marketing field. The 41 chapters that are divided into eight sections cover all aspects of contemporary interactive marketing realm, including social media and influencer marketing, big data and machine learning in predictive analytics, mobile marketing and proximity marketing, interactive digital marketing and Omnichannel marketing, AI, VR and AR in business applications. With a focal point on interactive marketing, this handbook takes a multidiscipline perspective, from new technology innovations, social media and platform application, economic and cultural impacts, social and psychological analysis, and management and information system. This book provides a timely and comprehensive textbook companion and/or course project resource for college educators and students used for variety of graduate and undergraduate marketing courses, such as Digital Marketing, Internet Marketing, Social Media Marketing, New Media Communication, Marketing Analytics and Marketing Management, etc. It offers valuable references for academic researchers who are interesting conducting and publishing in interactive marketing research. The state-of-art review and emerging new trends presented in the book are particularly useful for research idea generation and conceptual development. The book also putts forward insightful guidelines and practical tools for business management in the application of new interactive marketing strategies and applications in the real world practices. Chapter 41 “Ethical Considerations in Gamified Interactive Marketing Praxis” is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.

This first definitive reference resource to take a broad interdisciplinary approach to the nexus between music and the social and behavioral sciences examines how music affects human beings and their interactions in and with the world. The interdisciplinary nature of the work provides a starting place for students to situate the status of music within the social sciences in fields such as anthropology, communications, psychology, linguistics, sociology, sports, political science and economics, as well as biology and the health sciences. Features: Approximately 450 articles, arranged in A-to-Z fashion and richly illustrated with photographs, provide the social and behavioral context for examining the importance of music in society. Entries are authored and signed by experts in the field and conclude with references and further readings, as well as cross references to related entries. A Reader's Guide groups related entries by broad topic areas and themes, making it easy for readers to quickly identify related entries. A Chronology of Music places material into historical context; a Glossary defines key terms from the field; and a Resource Guide provides lists of books, academic journals, websites and cross-references. The multimedia digital edition is enhanced with video and audio clips and features strong search-and-browse capabilities through the electronic Reader’s Guide, detailed index, and cross references. Music in the Social and Behavioral Sciences, available in both multimedia digital and print formats, is a must-have reference for music and social science library collections.

This textbook provides both profound technological knowledge and a comprehensive treatment of essential topics in music processing and music information retrieval. Including numerous examples, figures, and exercises, this book is suited for students, lecturers, and researchers working in audio engineering, computer science, multimedia, and musicology. The book consists of eight chapters. The first two cover foundations of music representations and the Fourier transform—concepts that are then used throughout the book. In the subsequent chapters, concrete music processing tasks serve as a starting point. Each of these chapters is organized in a similar fashion and starts with a general description of the music processing scenario at hand before integrating it into a wider context. It then discusses—in a mathematically rigorous way—important techniques and algorithms that are generally applicable to a wide range of analysis, classification, and retrieval problems. At the same time, the techniques are directly applied to a specific music processing task. By mixing theory and practice, the book’s goal is to offer detailed technological insights as well as a deep understanding of music processing applications. Each chapter ends with a section that includes links to the research literature, suggestions for further reading, a list of references, and exercises. The chapters are organized in a modular fashion, thus offering lecturers and readers many ways to choose, rearrange or supplement the material. Accordingly, selected chapters or individual sections can easily be integrated into courses on general multimedia, information science, signal processing, music informatics, or the digital humanities.

This book constitutes the proceedings of the 15th IFIP TC8 International Conference on Computer Information Systems and Industrial Management, CISIM 2016, held in Vilnius, Lithuania, in September 2016. The 63 regular papers presented together with 1 inivted paper and 5 keynotes in this volume were carefully reviewed and selected from about 89 submissions. The main topics covered are rough set methods for big data analytics; images, visualization, classification; optimization, tuning; scheduling in manufacturing and other applications; algorithms; decisions; intelligent distributed systems; and biometrics, identification, security.

This first volume, edited and authored by world leading experts, gives a review of the principles, methods and techniques of important and emerging research topics and technologies in machine learning and advanced signal processing theory. With this reference source you will: - Quickly grasp a new area of research - Understand the underlying principles of a topic and its application - Ascertain how a topic relates to other areas and learn of the research issues yet to be resolved - Quick tutorial reviews of important and emerging topics of research in machine learning - Presents core principles in signal processing theory and shows their applications - Reference content on core principles, technologies, algorithms and applications - Comprehensive references to journal articles and other literature on which to build further, more specific and detailed knowledge - Edited by leading people in the field who, through their reputation, have been able to commission experts to write on a particular topic