Deep Learning for Music: A Systematic Literature Review

Recently, Artificial Intelligence development and implementation are becoming faster and more popular. Artificial Intelligence has appeared to help humans in their daily activities. Several examples that are currently hype are Chat-GPT, and AI Art. With the emergence of applications like Chat-GPT many people have started using applications that have Artificial Intelligence in it. However, there are still rare applications or research that discuss the implementation of Artificial Intelligence or deep learning in music. Therefore, this research will conduct a systematic literature review (SLR) on Deep Learning in music. In this systematic literature review we will research and answer three research questions. Those research question are, What kind of deep learning architecture that most widely used for developing, classifying, and making music; What implementations of deep learning can be done in music, Whether the existence of Artificial Intelligence / Deep learning can help musicians or composers in making music. Predetermined research questions will be answered using the Kitchenham & Cochrane method. From the results of the analysis that has been carried out we concluded that the deep learning methods that are widely used for training deep learning in music are CNN and RCNN, While the implementation of deep learning in music is used for classification and recommendation systems. For conclusion in this paper, we conclude that deep learning can be used to help musicians and composers in creating music.