Music Data Analysis


Music Data Analysis
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Music Data Analysis


Music Data Analysis
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Author : Claus Weihs
language : en
Publisher: CRC Press
Release Date : 2016-11-17

Music Data Analysis written by Claus Weihs and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-11-17 with Business & Economics categories.


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.



From Data To Decisions In Music Education Research


From Data To Decisions In Music Education Research
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Author : Brian C. Wesolowski
language : en
Publisher: Taylor & Francis
Release Date : 2022-02-22

From Data To Decisions In Music Education Research written by Brian C. Wesolowski and has been published by Taylor & Francis this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-02-22 with Music categories.


From Data to Decisions in Music Education Research provides a structured and hands-on approach to working with empirical data in the context of music education research. Using step-by-step tutorials with in-depth examples of music education data, this book draws upon concepts in data science and statistics to provide a comprehensive framework for working with a variety of data and solving data-driven problems. All of the skills presented here use the R programming language, a free, open-source statistical computing and graphics environment. Using R enables readers to refine their computational thinking abilities and data literacy skills while facilitating reproducibility, replication, and transparency of data analysis in the field. The book offers: A clear and comprehensive framework for thinking about data analysis processes in a music education context. An overview of common data structures and data types used in statistical programming and data analytics. Techniques for cleaning, preprocessing, manipulating, aggregating, and mining data in ways that facilitate organization and interpretation. Methods for summarizing and visualizing data to help identify structures, patterns, and trends within data sets. Detailed applications of descriptive, diagnostic, and predictive analytics processes. Step-by-step code for all concepts and analyses. Direct access to all data sets and R script files through the accompanying eResource. From Data to Decisions in Music Education Research offers a reference "cookbook" of code and programming recipes written with the graduate music education student in mind and breaks down data analysis processes and skills in an approachable fashion. It can be used across a wide range of graduate music education courses that rely on the application of empirical data analyses and will be useful to all music education scholars and professionals seeking to enhance their use of quantitative data.



Music Data Mining


Music Data Mining
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Author : Tao Li
language : en
Publisher: CRC Press
Release Date : 2011-07-12

Music Data Mining written by Tao Li and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-07-12 with Business & Economics categories.


The research area of music information retrieval has gradually evolved to address the challenges of effectively accessing and interacting large collections of music and associated data, such as styles, artists, lyrics, and reviews. Bringing together an interdisciplinary array of top researchers, Music Data Mining presents a variety of approaches to



From Data To Decisions In Music Education Research


From Data To Decisions In Music Education Research
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Author : Brian C. Wesolowski
language : en
Publisher: Routledge
Release Date : 2022-02-22

From Data To Decisions In Music Education Research written by Brian C. Wesolowski and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-02-22 with Music categories.


From Data to Decisions in Music Education Research provides a structured and hands-on approach to working with empirical data in the context of music education research. Using step-by-step tutorials with in-depth examples of music education data, this book draws upon concepts in data science and statistics to provide a comprehensive framework for working with a variety of data and solving data-driven problems. All of the skills presented here use the R programming language, a free, open-source statistical computing and graphics environment. Using R enables readers to refine their computational thinking abilities and data literacy skills while facilitating reproducibility, replication, and transparency of data analysis in the field. The book offers: A clear and comprehensive framework for thinking about data analysis processes in a music education context. An overview of common data structures and data types used in statistical programming and data analytics. Techniques for cleaning, preprocessing, manipulating, aggregating, and mining data in ways that facilitate organization and interpretation. Methods for summarizing and visualizing data to help identify structures, patterns, and trends within data sets. Detailed applications of descriptive, diagnostic, and predictive analytics processes. Step-by-step code for all concepts and analyses. Direct access to all data sets and R script files through the accompanying eResource. From Data to Decisions in Music Education Research offers a reference "cookbook" of code and programming recipes written with the graduate music education student in mind and breaks down data analysis processes and skills in an approachable fashion. It can be used across a wide range of graduate music education courses that rely on the application of empirical data analyses and will be useful to all music education scholars and professionals seeking to enhance their use of quantitative data.



Applications In Statistical Computing


Applications In Statistical Computing
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Author : Nadja Bauer
language : en
Publisher:
Release Date : 2019

Applications In Statistical Computing written by Nadja Bauer and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019 with Electronic books categories.


This volume presents a selection of research papers on various topics at the interface of statistics and computer science. Emphasis is put on the practical applications of statistical methods in various disciplines, using machine learning and other computational methods. The book covers fields of research including the design of experiments, computational statistics, music data analysis, statistical process control, biometrics, industrial engineering, and econometrics. Gathering innovative, high-quality and scientifically relevant contributions, the volume was published in honor of Claus Weihs, Professor of Computational Statistics at TU Dortmund University, on the occasion of his 66th birthday.



Music Data Analysis


Music Data Analysis
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Author : Claus Weihs
language : en
Publisher: CRC Press
Release Date : 2016-11-17

Music Data Analysis written by Claus Weihs and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-11-17 with Business & Economics categories.


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.



Entertainment Science


Entertainment Science
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Author : Thorsten Hennig-Thurau
language : en
Publisher: Springer
Release Date : 2018-08-01

Entertainment Science written by Thorsten Hennig-Thurau and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-08-01 with Business & Economics categories.


The entertainment industry has long been dominated by legendary screenwriter William Goldman’s “Nobody-Knows-Anything” mantra, which argues that success is the result of managerial intuition and instinct. This book builds the case that combining such intuition with data analytics and rigorous scholarly knowledge provides a source of sustainable competitive advantage – the same recipe for success that is behind the rise of firms such as Netflix and Spotify, but has also fueled Disney’s recent success. Unlocking a large repertoire of scientific studies by business scholars and entertainment economists, the authors identify essential factors, mechanisms, and methods that help a new entertainment product succeed. The book thus offers a timely alternative to “Nobody-Knows” decision-making in the digital era: while coupling a good idea with smart data analytics and entertainment theory cannot guarantee a hit, it systematically and substantially increases the probability of success in the entertainment industry. Entertainment Science is poised to inspire fresh new thinking among managers, students of entertainment, and scholars alike. Thorsten Hennig-Thurau and Mark B. Houston – two of our finest scholars in the area of entertainment marketing – have produced a definitive research-based compendium that cuts across various branches of the arts to explain the phenomena that provide consumption experiences to capture the hearts and minds of audiences. Morris B. Holbrook, W. T. Dillard Professor Emeritus of Marketing, Columbia University Entertainment Science is a must-read for everyone working in the entertainment industry today, where the impact of digital and the use of big data can’t be ignored anymore. Hennig-Thurau and Houston are the scientific frontrunners of knowledge that the industry urgently needs. Michael Kölmel, media entrepreneur and Honorary Professor of Media Economics at University of Leipzig Entertainment Science’s winning combination of creativity, theory, and data analytics offers managers in the creative industries and beyond a novel, compelling, and comprehensive approach to support their decision-making. This ground-breaking book marks the dawn of a new Golden Age of fruitful conversation between entertainment scholars, managers, and artists. Allègre Hadida, Associate Professor in Strategy, University of Cambridge



The Music In The Data


The Music In The Data
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Author : Christopher White
language : en
Publisher: Taylor & Francis
Release Date : 2022-12-28

The Music In The Data written by Christopher White and has been published by Taylor & Francis this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-12-28 with Music categories.


Putting forward an extensive new argument for a humanities-based approach to big-data analysis, The Music in the Data shows how large datasets of music, or music corpora, can be productively integrated with the qualitative questions at the heart of music research. The author argues that as well as providing objective evidence, music corpora can themselves be treated as texts to be subjectively read and creatively interpreted, allowing new levels of understanding and insight into music traditions. Each chapter in this book asks how we define a core music-theory topic, such as style, harmony, meter, function, and musical key, and then approaches the topic through considering trends within large musical datasets, applying a combination of quantitative analysis and qualitative interpretation. Throughout, several basic techniques of data analysis are introduced and explained, with supporting materials available online. Connecting the empirical information from corpus analysis with theories of musical and textual meaning, and showing how each approach can enrich the other, this book provides a vital perspective for scholars and students in music theory, musicology, and all areas of music research.



Sentiment Analysis Of Music Using Statistics And Machine Learning


Sentiment Analysis Of Music Using Statistics And Machine Learning
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Author : Aakash Mukherjee
language : en
Publisher: Sanctum Books
Release Date : 2022-10-16

Sentiment Analysis Of Music Using Statistics And Machine Learning written by Aakash Mukherjee and has been published by Sanctum Books this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-10-16 with Music categories.


Sentiment analysis and prediction of contemporary Music can have a wide range of applications in modern society, for instance, selecting music for public institutions such as hospitals or restaurants to potentially improve the emotional well-being of personnel, patients, and customers respectively. In this project, a music recommendation system is built upon a Naive Bayes Classifier trained to predict the sentiment of songs based on song lyrics alone. Online streaming platforms have become one of the most important forms of music consumption. Most streaming platforms provide tools to assess the popularity of a song in the forms of scores and rankings. In this book, we address two issues related to song popularity. First, we predict whether an already popular song may attract higher-than-average public interest and become viral. Second, we predict whether sudden spikes in the public interest will translate into long-term popularity growth. We base our findings on data from the streaming platform Billboard, Spotify, and consider appearances in its "Most-Popular" list as indicative of popularity, and appearances in its "Virals" list as indicative of interest growth. We approach the problem as a classification task and employ a Support Vector Machine model built on popularity information to predict interest, and vice versa.



Applications In Statistical Computing


Applications In Statistical Computing
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Author : Nadja Bauer
language : en
Publisher: Springer Nature
Release Date : 2019-10-12

Applications In Statistical Computing written by Nadja Bauer and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-10-12 with Computers categories.


This volume presents a selection of research papers on various topics at the interface of statistics and computer science. Emphasis is put on the practical applications of statistical methods in various disciplines, using machine learning and other computational methods. The book covers fields of research including the design of experiments, computational statistics, music data analysis, statistical process control, biometrics, industrial engineering, and econometrics. Gathering innovative, high-quality and scientifically relevant contributions, the volume was published in honor of Claus Weihs, Professor of Computational Statistics at TU Dortmund University, on the occasion of his 66th birthday.