Szczegóły publikacji

Opis bibliograficzny

Artificial intelligence in music: recent trends and challenges / Jan Mycka, Jacek MAŃDZIUK // Neural Computing & Applications ; ISSN  0941-0643 . — 2025 — vol. 37 iss. 2, s. 801–839. — Bibliogr. s. 833–839, Abstr. — Publikacja dostępna online od: 2024-11-16. — J. Mańdziuk - dod. afiliacja: Warsaw University of Technology

Autorzy (2)

Słowa kluczowe

music recommendationAI in musicmusic classificationmusic generation

Dane bibliometryczne

ID BaDAP166156
Data dodania do BaDAP2026-02-20
Tekst źródłowyURL
DOI10.1007/s00521-024-10555-x
Rok publikacji2025
Typ publikacjiartykuł w czasopiśmie
Otwarty dostęptak
Creative Commons
Czasopismo/seriaNeural Computing & Applications

Abstract

Music has always been an essential aspect of human culture, and the methods for its creation and analysis have evolved alongside the advancement of computational capabilities. With the emergence of artificial intelligence (AI) and one of its major goals referring to mimicking human creativity, the interest in music-related research has increased significantly. This review examines current literature from renowned journals and top-tier conferences, published between 2017 and 2023, regarding the application of AI to music-related topics. The study proposes a division of AI-in-music research into three major categories: music classification, music generation and music recommendation. Each category is segmented into smaller thematic areas, with detailed analysis of their inter- and intra-similarities and differences. The second part of the study is devoted to the presentation of the AI methods employed, with specific attention given to deep neural networks—the prevailing approach in this domain, nowadays. In addition, real-life applications and copyright aspects of generated music are outlined. We believe that a detailed presentation of the field along with pointing out possible future challenges in the area will be of some value for both the established AI-in-music researchers, as well as the new scholars entering this fascinating field.

Publikacje, które mogą Cię zainteresować

artykuł
#164421Data dodania: 27.11.2025
Cybersecurity challenges and opportunities of machine learning-based artificial intelligence / Paweł Czaja, Bartłomiej GDOWSKI, Marcin NIEMIEC, Wim Mees, Nikolai Stoianov, Konstantinos Votis, Vyacheslav Kharchenko, Vasilis Katos, Matteo Merialdo // Neural Computing & Applications ; ISSN 0941-0643. — 2025 — vol. 37 iss. 33, s. 27931–27956. — Bibliogr. s. 27952–27956, Abstr. — Publikacja dostępna online od: 2025-10-08
fragment książki
#3446Data dodania: 18.4.2001
Simulation and artificial intelligence in business process reengineering/improvement / Andrzej MACIOŁ, Jerzy DUDA // W: Neural networks and soft computing : proceedings of the fifth conference : Zakopane, Poland June 6–10, 2000 / eds. L. Rutkowski, R. Tadeusiewicz ; Polish Neural Network Society in cooperation with IEEE Neural Networks Council and Department of Computer Engineering Technical University of Częstochowa. — Częstochowa : PNNS, 2000. — S. 585–590. — Bibliogr. s. 590, Abstr.