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Harmonizing minds and machines: survey on transformative power of machine learning in music

This survey explores the symbiotic relationship between Machine Learning (ML) and music, focusing on the transformative role of Artificial Intelligence (AI) in the musical sphere. Beginning with a historical contextualization of the intertwined trajectories of music and technology, the paper discuss...

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Detalles Bibliográficos
Autor principal: Liang, Jing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10668594/
https://www.ncbi.nlm.nih.gov/pubmed/38023456
http://dx.doi.org/10.3389/fnbot.2023.1267561
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author Liang, Jing
author_facet Liang, Jing
author_sort Liang, Jing
collection PubMed
description This survey explores the symbiotic relationship between Machine Learning (ML) and music, focusing on the transformative role of Artificial Intelligence (AI) in the musical sphere. Beginning with a historical contextualization of the intertwined trajectories of music and technology, the paper discusses the progressive use of ML in music analysis and creation. Emphasis is placed on present applications and future potential. A detailed examination of music information retrieval, automatic music transcription, music recommendation, and algorithmic composition presents state-of-the-art algorithms and their respective functionalities. The paper underscores recent advancements, including ML-assisted music production and emotion-driven music generation. The survey concludes with a prospective contemplation of future directions of ML within music, highlighting the ongoing growth, novel applications, and anticipation of deeper integration of ML across musical domains. This comprehensive study asserts the profound potential of ML to revolutionize the musical landscape and encourages further exploration and advancement in this emerging interdisciplinary field.
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spelling pubmed-106685942023-01-01 Harmonizing minds and machines: survey on transformative power of machine learning in music Liang, Jing Front Neurorobot Neuroscience This survey explores the symbiotic relationship between Machine Learning (ML) and music, focusing on the transformative role of Artificial Intelligence (AI) in the musical sphere. Beginning with a historical contextualization of the intertwined trajectories of music and technology, the paper discusses the progressive use of ML in music analysis and creation. Emphasis is placed on present applications and future potential. A detailed examination of music information retrieval, automatic music transcription, music recommendation, and algorithmic composition presents state-of-the-art algorithms and their respective functionalities. The paper underscores recent advancements, including ML-assisted music production and emotion-driven music generation. The survey concludes with a prospective contemplation of future directions of ML within music, highlighting the ongoing growth, novel applications, and anticipation of deeper integration of ML across musical domains. This comprehensive study asserts the profound potential of ML to revolutionize the musical landscape and encourages further exploration and advancement in this emerging interdisciplinary field. Frontiers Media S.A. 2023-11-10 /pmc/articles/PMC10668594/ /pubmed/38023456 http://dx.doi.org/10.3389/fnbot.2023.1267561 Text en Copyright © 2023 Liang. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Neuroscience
Liang, Jing
Harmonizing minds and machines: survey on transformative power of machine learning in music
title Harmonizing minds and machines: survey on transformative power of machine learning in music
title_full Harmonizing minds and machines: survey on transformative power of machine learning in music
title_fullStr Harmonizing minds and machines: survey on transformative power of machine learning in music
title_full_unstemmed Harmonizing minds and machines: survey on transformative power of machine learning in music
title_short Harmonizing minds and machines: survey on transformative power of machine learning in music
title_sort harmonizing minds and machines: survey on transformative power of machine learning in music
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10668594/
https://www.ncbi.nlm.nih.gov/pubmed/38023456
http://dx.doi.org/10.3389/fnbot.2023.1267561
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