DEVELOPMENT OF A MUSIC GENERATION ALGORITHM

Le résumé fourni par la source

This paper presents a developed music generation algorithm based on deep machine learning techniques. The algorithm uses datasets from different music genres to train the model and generate new music compositions. The paper presents the main stages of algorithm development, including data collection and preprocessing, selection and tuning of the model architecture, definition of loss and activation functions, and selection of the optimizer. Experimental results demonstrating the effectiveness of the developed algorithm in music generation are presented. This paper is of interest to researchers in machine learning and computer music, as well as to musicians and composers looking for new ideas for music generation.

Ce résumé expose les affirmations des auteurs. BNTIC ne l’interprète pas comme une validation indépendante des résultats.