Deep Learning Techniques For Music Generation

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Deep Learning Techniques For Music Generation

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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

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Author : Alexandre DuBreuil
language : en
Publisher:
Release Date : 2020-01-30

Hands On Music Generation With Magenta written by Alexandre DuBreuil and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-01-30 with Computers categories.

Design and use machine learning models for music generation using Magenta and make them interact with existing music creation tools Key Features Learn how machine learning, deep learning, and reinforcement learning are used in music generation Generate new content by manipulating the source data using Magenta utilities, and train machine learning models with it Explore various Magenta projects such as Magenta Studio, MusicVAE, and NSynth Book 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 learn Use RNN models in Magenta to generate MIDI percussion, and monophonic and polyphonic sequences Use WaveNet and GAN models to generate instrument notes in the form of raw audio Employ Variational Autoencoder models like MusicVAE and GrooVAE to sample, interpolate, and humanize existing sequences Prepare and create your dataset on specific styles and instruments Train your network on your personal datasets and fix problems when training networks Apply MIDI to synchronize Magenta with existing music production tools like DAWs Who 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.

Music Emotion Recognition

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Author : Yi-Hsuan Yang
language : en
Publisher: CRC Press
Release Date : 2011-02-22

Music Emotion Recognition written by Yi-Hsuan Yang and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-02-22 with Computers categories.

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

Storytelling With Data

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Author : Cole Nussbaumer Knaflic
language : en
Publisher: John Wiley & Sons
Release Date : 2015-10-09

Storytelling With Data written by Cole Nussbaumer Knaflic and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-10-09 with Mathematics categories.

Don't simply show your data—tell a story with it! Storytelling with Data teaches you the fundamentals of data visualization and how to communicate effectively with data. You'll discover the power of storytelling and the way to make data a pivotal point in your story. The lessons in this illuminative text are grounded in theory, but made accessible through numerous real-world examples—ready for immediate application to your next graph or presentation. Storytelling is not an inherent skill, especially when it comes to data visualization, and the tools at our disposal don't make it any easier. This book demonstrates how to go beyond conventional tools to reach the root of your data, and how to use your data to create an engaging, informative, compelling story. Specifically, you'll learn how to: Understand the importance of context and audience Determine the appropriate type of graph for your situation Recognize and eliminate the clutter clouding your information Direct your audience's attention to the most important parts of your data Think like a designer and utilize concepts of design in data visualization Leverage the power of storytelling to help your message resonate with your audience Together, the lessons in this book will help you turn your data into high impact visual stories that stick with your audience. Rid your world of ineffective graphs, one exploding 3D pie chart at a time. There is a story in your data—Storytelling with Data will give you the skills and power to tell it!

Deep Learning Projects Using Tensorflow 2

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Author : Vinita Silaparasetty
language : en
Publisher: Apress
Release Date : 2020-08-08

Deep Learning Projects Using Tensorflow 2 written by Vinita Silaparasetty and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-08-08 with Computers categories.

Work through engaging and practical deep learning projects using TensorFlow 2.0. Using a hands-on approach, the projects in this book will lead new programmers through the basics into developing practical deep learning applications. Deep learning is quickly integrating itself into the technology landscape. Its applications range from applicable data science to deep fakes and so much more. It is crucial for aspiring data scientists or those who want to enter the field of AI to understand deep learning concepts. The best way to learn is by doing. You'll develop a working knowledge of not only TensorFlow, but also related technologies such as Python and Keras. You'll also work with Neural Networks and other deep learning concepts. By the end of the book, you'll have a collection of unique projects that you can add to your GitHub profiles and expand on for professional application. What You'll Learn Grasp the basic process of neural networks through projects, such as creating music Restore and colorize black and white images with deep learning processes Who This Book Is For Beginners new to TensorFlow and Python.

High Performance Computing And Networking

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Author : Ch. Satyanarayana
language : en
Publisher: Springer Nature
Release Date : 2022-03-22

High Performance Computing And Networking written by Ch. Satyanarayana and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-03-22 with Computers categories.

This book comprises the proceedings of the 2nd International Conference on Computer Vision, High-Performance Computing, Smart Devices, and Networks (CHSN 2021). This book highlights the high-quality research articles in machine learning, computer vision, and networks. The content of this volume gives the reader an up-to-date picture of the state-of-the-art connection between computational intelligence, machine learning, and IoT. The papers included in this volume are peer-reviewed by experts in the related areas. The book will serve as a valuable reference resource for academics and researchers across the globe.

Advances In Neural Computation Machine Learning And Cognitive Research Viii

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Author : Vladimir Redko
language : en
Publisher: Springer Nature
Release Date : 2025-02-28

Advances In Neural Computation Machine Learning And Cognitive Research Viii written by Vladimir Redko and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-02-28 with Computers categories.

This book describes new theories and applications of artificial neural networks, with a special focus on answering questions in neuroscience, biology and biophysics and cognitive research. It covers a wide range of methods and technologies, including deep neural networks, large-scale neural models, brain–computer interface, signal processing methods, as well as models of perception, studies on emotion recognition, self-organization and many more. The book includes both selected and invited papers presented at the XXVI International Conference on Neuroinformatics, held on October 21–25, 2024, in Moscow, Russia.

Law And Artificial Intelligence

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Author : Bart Custers
language : en
Publisher: Springer Nature
Release Date : 2022-07-05

Law And Artificial Intelligence written by Bart Custers and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-07-05 with Law categories.

This book provides an in-depth overview of what is currently happening in the field of Law and Artificial Intelligence (AI). From deep fakes and disinformation to killer robots, surgical robots, and AI lawmaking, the many and varied contributors to this volume discuss how AI could and should be regulated in the areas of public law, including constitutional law, human rights law, criminal law, and tax law, as well as areas of private law, including liability law, competition law, and consumer law. Aimed at an audience without a background in technology, this book covers how AI changes these areas of law as well as legal practice itself. This scholarship should prove of value to academics in several disciplines (e.g., law, ethics, sociology, politics, and public administration) and those who may find themselves confronted with AI in the course of their work, particularly people working within the legal domain (e.g., lawyers, judges, law enforcement officers, public prosecutors, lawmakers, and policy advisors). Bart Custers is Professor of Law and Data Science at eLaw - Center for Law and Digital Technologies at Leiden University in the Netherlands. Eduard Fosch-Villaronga is Assistant Professor at eLaw - Center for Law and Digital Technologies at Leiden University in the Netherlands.

Deep Learning

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Author : Li Deng
language : en
Publisher:
Release Date : 2014

Deep Learning written by Li Deng and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014 with Machine learning categories.

Provides an overview of general deep learning methodology and its applications to a variety of signal and information processing tasks

Algorithms And Architectures For Parallel Processing

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Author : Tianqing Zhu
language : en
Publisher: Springer Nature
Release Date : 2025-02-14

Algorithms And Architectures For Parallel Processing written by Tianqing Zhu and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-02-14 with Computers categories.

The six-volume set, LNCS 15251-15256, constitutes the refereed proceedings of the 24th International Conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2024, held in Macau, China, during October 29–31, 2024. The 91 full papers, 35 short papers and 5 workshop papers included in these proceedings were carefully reviewed and selected from 265 submissions. They focus on the many dimensions of parallel algorithms and architectures, encompassing fundamental theoretical approaches, practical experimental projects, and commercial components and systems.