Machine Learning And 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.

Machine Learning And Music Generation

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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.

Hands On Music Generation With Magenta

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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

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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.

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.

Artificial Intelligence In Music Sound Art And Design

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Author : Colin Johnson
language : en
Publisher: Springer Nature
Release Date : 2023-03-31

Artificial Intelligence In Music Sound Art And Design written by Colin Johnson and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-03-31 with Computers categories.

This book constitutes the refereed proceedings of the 12th European Conference on Artificial Intelligence in Music, Sound, Art and Design, EvoMUSART 2023, held as part of Evo* 2023, in April 2023, co-located with the Evo* 2023 events, EvoCOP, EvoApplications, and EuroGP. The 20 full papers and 7 short papers presented in this book were carefully reviewed and selected from 55 submissions. They cover a wide range of topics and application areas of artificial intelligence, including generative approaches to music and visual art, deep learning, and architecture.

Power Devices And Internet Of Things For Intelligent System Design

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Author : Angsuman Sarkar
language : en
Publisher: John Wiley & Sons
Release Date : 2025-02-26

Power Devices And Internet Of Things For Intelligent System Design written by Angsuman Sarkar 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 2025-02-26 with Computers categories.

Artificial Intelligence And Machine Learning

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Author : Toon Calders
language : en
Publisher: Springer Nature
Release Date : 2023-09-04

Artificial Intelligence And Machine Learning written by Toon Calders and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-09-04 with Computers categories.

This book contains a selection of the best papers of the 34th Benelux Conference on Artificial Intelligence, BNAIC/ BENELEARN 2022, held in Mechelen, Belgium, in November 2022. The 11 papers presented in this volume were carefully reviewed and selected from 134 regular submissions. They address various aspects of artificial intelligence such as natural language processing, agent technology, game theory, problem solving, machine learning, human-agent interaction, AI and education, and data analysis.

Artificial Intelligence In Music Sound Art And Design

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Author : Tiago Martins
language : en
Publisher: Springer Nature
Release Date : 2022-04-15

Artificial Intelligence In Music Sound Art And Design written by Tiago Martins and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-04-15 with Computers categories.

This book constitutes the refereed proceedings of the 10th European Conference on Artificial Intelligence in Music, Sound, Art and Design, EvoMUSART 2022, held as part of Evo* 2022, in April 2022, co-located with the Evo* 2022 events, EvoCOP, EvoApplications, and EuroGP. The 20 full papers and 6 short papers presented in this book were carefully reviewed and selected from 66 submissions. They cover a wide range of topics and application areas, including generative approaches to music and visual art, deep learning, and architecture.

Deep Learning Research Applications For Natural Language Processing

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Author : Ashok Kumar, L.
language : en
Publisher: IGI Global
Release Date : 2022-12-09

Deep Learning Research Applications For Natural Language Processing written by Ashok Kumar, L. and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-12-09 with Computers categories.

Humans have the most advanced method of communication, which is known as natural language. While humans can use computers to send voice and text messages to each other, computers do not innately know how to process natural language. In recent years, deep learning has primarily transformed the perspectives of a variety of fields in artificial intelligence (AI), including speech, vision, and natural language processing (NLP). The extensive success of deep learning in a wide variety of applications has served as a benchmark for the many downstream tasks in AI. The field of computer vision has taken great leaps in recent years and surpassed humans in tasks related to detecting and labeling objects thanks to advances in deep learning and neural networks. Deep Learning Research Applications for Natural Language Processing explains the concepts and state-of-the-art research in the fields of NLP, speech, and computer vision. It provides insights into using the tools and libraries in Python for real-world applications. Covering topics such as deep learning algorithms, neural networks, and advanced prediction, this premier reference source is an excellent resource for computational linguists, software engineers, IT managers, computer scientists, students and faculty of higher education, libraries, researchers, and academicians.