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A DEEP LEARNING BASED INNOVATIVE ONLINE MUSIC PRODUCTION FRAMEWORK

摘要


In this research, we constructed an online music production process framework to explain the operation of the industry and conduct comparative analysis, competitive analysis, and innovative business model analysis for the current music industry situation. This research can provide strategic suggestions for future scholars and industry development. In this study, through the concept of the internet, we propose the framework process of a deep learning music production (DLMP) system, and each work process and the main work content of each module in the system are described. We used upstream, midstream, and downstream industry roles for comparison and used an innovative operating model to describe the overall industry transformation. Through this research, we can more clearly see a blueprint for the future development of music production and can provide operators with a competitive advantage strategy.

參考文獻


S.-S. Weng and H.-C. Chen, "Exploring the role of deep learning technology in the sustainable development of the music production industry," Sustainability, Vol. 12, No. 2, p. 625, 2020.
A. H. Weis, "Commercialization of the internet," Internet Research, Vol. 20, pp. 420-435, 2010.
G. Graham, B. Burnes, G. J. Lewis, and J. Langer, "The transformation of the music industry supply chain: A major label perspective," International Journal of Operations & Production Management, Vol. 24, pp. 1087-1103, 2004.
P. M. C. Swatman, C. Krueger, and K. van der Beek, "The changing digital content landscape: An evaluation of e‐business model development in European online news and music," Internet Research, Vol. 16, pp. 53-80, 2006.
R. Viglianti, "Musicxml: an xml based approach to musicological analysis," in Digital Humanities 2007: Conference Abstracts, pp. 235-37, 2007.

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