Machine Learning And Music Generation
DOWNLOAD eBooks
Download Machine Learning And Music Generation PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Machine Learning And Music Generation book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages. If the content not found or just blank you must refresh this page
Deep Learning Techniques For Music Generation
DOWNLOAD eBooks
Author : Jean-Pierre Briot
language : en
Publisher: Springer
Release Date : 2019-11-08
Deep Learning Techniques For Music Generation written by Jean-Pierre Briot and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-08 with Computers categories.
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.
Hands On Music Generation With Magenta
DOWNLOAD eBooks
Author : Alexandre DuBreuil
language : en
Publisher: Packt Publishing Ltd
Release Date : 2020-01-31
Hands On Music Generation With Magenta written by Alexandre DuBreuil and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-01-31 with Mathematics categories.
Design and use machine learning models for music generation using Magenta and make them interact with existing music creation tools Key FeaturesLearn how machine learning, deep learning, and reinforcement learning are used in music generationGenerate new content by manipulating the source data using Magenta utilities, and train machine learning models with itExplore various Magenta projects such as Magenta Studio, MusicVAE, and NSynthBook Description The importance of machine learning (ML) in art is growing at a rapid pace due to recent advancements in the field, and Magenta is at the forefront of this innovation. With this book, you’ll follow a hands-on approach to using ML models for music generation, learning how to integrate them into an existing music production workflow. Complete with practical examples and explanations of the theoretical background required to understand the underlying technologies, this book is the perfect starting point to begin exploring music generation. The book will help you learn how to use the models in Magenta for generating percussion sequences, monophonic and polyphonic melodies in MIDI, and instrument sounds in raw audio. Through practical examples and in-depth explanations, you’ll understand ML models such as RNNs, VAEs, and GANs. Using this knowledge, you’ll create and train your own models for advanced music generation use cases, along with preparing new datasets. Finally, you’ll get to grips with integrating Magenta with other technologies, such as digital audio workstations (DAWs), and using Magenta.js to distribute music generation apps in the browser. By the end of this book, you'll be well-versed with Magenta and have developed the skills you need to use ML models for music generation in your own style. What you will learnUse RNN models in Magenta to generate MIDI percussion, and monophonic and polyphonic sequencesUse WaveNet and GAN models to generate instrument notes in the form of raw audioEmploy Variational Autoencoder models like MusicVAE and GrooVAE to sample, interpolate, and humanize existing sequencesPrepare and create your dataset on specific styles and instrumentsTrain your network on your personal datasets and fix problems when training networksApply MIDI to synchronize Magenta with existing music production tools like DAWsWho this book is for This book is for technically inclined artists and musically inclined computer scientists. Readers who want to get hands-on with building generative music applications that use deep learning will also find this book useful. Although prior musical or technical competence is not required, basic knowledge of the Python programming language is assumed.
Machine Learning And Music Generation
DOWNLOAD eBooks
Author : José M. Iñesta
language : en
Publisher: Routledge
Release Date : 2018-10-16
Machine Learning And Music Generation written by José M. Iñesta and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-10-16 with Mathematics categories.
Computational approaches to music composition and style imitation have engaged musicians, music scholars, and computer scientists since the early days of computing. Music generation research has generally employed one of two strategies: knowledge-based methods that model style through explicitly formalized rules, and data mining methods that apply machine learning to induce statistical models of musical style. The five chapters in this book illustrate the range of tasks and design choices in current music generation research applying machine learning techniques and highlighting recurring research issues such as training data, music representation, candidate generation, and evaluation. The contributions focus on different aspects of modeling and generating music, including melody, chord sequences, ornamentation, and dynamics. Models are induced from audio data or symbolic data. This book was originally published as a special issue of the Journal of Mathematics and Music.
Algorithmic Composition
DOWNLOAD eBooks
Author : Gerhard Nierhaus
language : en
Publisher: Springer Science & Business Media
Release Date : 2009-08-28
Algorithmic Composition written by Gerhard Nierhaus and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-08-28 with Mathematics categories.
Algorithmic composition – composing by means of formalizable methods – has a century old tradition not only in occidental music history. This is the first book to provide a detailed overview of prominent procedures of algorithmic composition in a pragmatic way rather than by treating formalizable aspects in single works. In addition to an historic overview, each chapter presents a specific class of algorithm in a compositional context by providing a general introduction to its development and theoretical basis and describes different musical applications. Each chapter outlines the strengths, weaknesses and possible aesthetical implications resulting from the application of the treated approaches. Topics covered are: markov models, generative grammars, transition networks, chaos and self-similarity, genetic algorithms, cellular automata, neural networks and artificial intelligence are covered. The comprehensive bibliography makes this work ideal for the musician and the researcher alike.
Generative Deep Learning
DOWNLOAD eBooks
Author : David Foster
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2019-06-28
Generative Deep Learning written by David Foster and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-06-28 with Computers categories.
Generative modeling is one of the hottest topics in AI. It’s now possible to teach a machine to excel at human endeavors such as painting, writing, and composing music. With this practical book, machine-learning engineers and data scientists will discover how to re-create some of the most impressive examples of generative deep learning models, such as variational autoencoders,generative adversarial networks (GANs), encoder-decoder models and world models. Author David Foster demonstrates the inner workings of each technique, starting with the basics of deep learning before advancing to some of the most cutting-edge algorithms in the field. Through tips and tricks, you’ll understand how to make your models learn more efficiently and become more creative. Discover how variational autoencoders can change facial expressions in photos Build practical GAN examples from scratch, including CycleGAN for style transfer and MuseGAN for music generation Create recurrent generative models for text generation and learn how to improve the models using attention Understand how generative models can help agents to accomplish tasks within a reinforcement learning setting Explore the architecture of the Transformer (BERT, GPT-2) and image generation models such as ProGAN and StyleGAN
Mathematical Music
DOWNLOAD eBooks
Author : Nikita Braguinski
language : en
Publisher: CRC Press
Release Date : 2022-03-13
Mathematical Music written by Nikita Braguinski and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-03-13 with Mathematics categories.
Mathematical Music offers a concise and easily accessible history of how mathematics was used to create music. The story presented in this short, engaging volume ranges from ratios in antiquity to random combinations in the 17th century, 20th-century statistics, and contemporary artificial intelligence. This book provides a fascinating panorama of the gradual mechanization of thought processes involved in the creation of music. How did Baroque authors envision a composition system based on combinatorics? What was it like to create musical algorithms at the beginning of the 20th century, before the computer became a reality? And how does this all explain today’s use of artificial intelligence and machine learning in music? In addition to discussing the history and the present state of mathematical music, Braguinski also takes a look at what possibilities the near future of music AI might hold for listeners, musicians, and the society. Grounded in research findings from musicology and the history of technology, and written for the non-specialist general audience, this book helps both student and professional readers to make sense of today’s music AI by situating it in a continuous historical context.
Deep And Shallow
DOWNLOAD eBooks
Author : Shlomo Dubnov
language : en
Publisher: CRC Press
Release Date : 2023-12-08
Deep And Shallow written by Shlomo Dubnov and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-12-08 with Computers categories.
Providing an essential and unique bridge between the theories of signal processing, machine learning, and artificial intelligence (AI) in music, this book provides a holistic overview of foundational ideas in music, from the physical and mathematical properties of sound to symbolic representations. Combining signals and language models in one place, this book explores how sound may be represented and manipulated by computer systems, and how our devices may come to recognize particular sonic patterns as musically meaningful or creative through the lens of information theory. Introducing popular fundamental ideas in AI at a comfortable pace, more complex discussions around implementations and implications in musical creativity are gradually incorporated as the book progresses. Each chapter is accompanied by guided programming activities designed to familiarize readers with practical implications of discussed theory, without the frustrations of free-form coding. Surveying state-of-the art methods in applications of deep neural networks to audio and sound computing, as well as offering a research perspective that suggests future challenges in music and AI research, this book appeals to both students of AI and music, as well as industry professionals in the fields of machine learning, music, and AI.
Generative Ai With Python And Tensorflow 2
DOWNLOAD eBooks
Author : Joseph Babcock
language : en
Publisher: Packt Publishing Ltd
Release Date : 2021-04-30
Generative Ai With Python And Tensorflow 2 written by Joseph Babcock and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-04-30 with Computers categories.
Fun and exciting projects to learn what artificial minds can create Key FeaturesCode examples are in TensorFlow 2, which make it easy for PyTorch users to follow alongLook inside the most famous deep generative models, from GPT to MuseGANLearn to build and adapt your own models in TensorFlow 2.xExplore exciting, cutting-edge use cases for deep generative AIBook Description Machines are excelling at creative human skills such as painting, writing, and composing music. Could you be more creative than generative AI? In this book, you’ll explore the evolution of generative models, from restricted Boltzmann machines and deep belief networks to VAEs and GANs. You’ll learn how to implement models yourself in TensorFlow and get to grips with the latest research on deep neural networks. There’s been an explosion in potential use cases for generative models. You’ll look at Open AI’s news generator, deepfakes, and training deep learning agents to navigate a simulated environment. Recreate the code that’s under the hood and uncover surprising links between text, image, and music generation. What you will learnExport the code from GitHub into Google Colab to see how everything works for yourselfCompose music using LSTM models, simple GANs, and MuseGANCreate deepfakes using facial landmarks, autoencoders, and pix2pix GANLearn how attention and transformers have changed NLPBuild several text generation pipelines based on LSTMs, BERT, and GPT-2Implement paired and unpaired style transfer with networks like StyleGANDiscover emerging applications of generative AI like folding proteins and creating videos from imagesWho this book is for This is a book for Python programmers who are keen to create and have some fun using generative models. To make the most out of this book, you should have a basic familiarity with math and statistics for machine learning.
Proceedings Of International Conference On Computational Intelligence Data Science And Cloud Computing
DOWNLOAD eBooks
Author : Valentina Emilia Balas
language : en
Publisher: Springer Nature
Release Date : 2021
Proceedings Of International Conference On Computational Intelligence Data Science And Cloud Computing written by Valentina Emilia Balas and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021 with Artificial intelligence categories.
This book includes selected papers presented at International Conference on Computational Intelligence, Data Science and Cloud Computing (IEM-ICDC) 2020, organized by the Department of Information Technology, Institute of Engineering & Management, Kolkata, India, during 25-27 September 2020. It presents substantial new research findings about AI and robotics, image processing and NLP, cloud computing and big data analytics as well as in cyber security, blockchain and IoT, and various allied fields. The book serves as a reference resource for researchers and practitioners in academia and industry.
Soft Computing And Signal Processing
DOWNLOAD eBooks
Author : Jiacun Wang
language : en
Publisher: Springer
Release Date : 2019-02-13
Soft Computing And Signal Processing written by Jiacun Wang and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-02-13 with Technology & Engineering categories.
The book includes research papers on current developments in the field of soft computing and signal processing, selected from papers presented at the International Conference on Soft Computing and Signal Processing (ICSCSP 2018). It features papers on current topics, such as soft sets, rough sets, fuzzy logic, neural networks, genetic algorithms and machine learning. It also discusses various aspects of these topics, like technologies, product implementation, and application issues.