Interactive Melody Generation System for Enhancing the Creativity of Musicians

• URL: http://arxiv.org/abs/2403.03395v1
• Date: Wed, 6 Mar 2024 01:33:48 GMT
• Title: Interactive Melody Generation System for Enhancing the Creativity of Musicians
• Authors: So Hirawata and Noriko Otani
• Abstract summary: This study proposes a system designed to enumerate the process of collaborative composition among humans. By integrating multiple Recurrent Neural Network (RNN) models, the system provides an experience akin to collaborating with several composers.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: This study proposes a system designed to enumerate the process of collaborative composition among humans, using automatic music composition technology. By integrating multiple Recurrent Neural Network (RNN) models, the system provides an experience akin to collaborating with several composers, thereby fostering diverse creativity. Through dynamic adaptation to the user's creative intentions, based on feedback, the system enhances its capability to generate melodies that align with user preferences and creative needs. The system's effectiveness was evaluated through experiments with composers of varying backgrounds, revealing its potential to facilitate musical creativity and suggesting avenues for further refinement. The study underscores the importance of interaction between the composer and AI, aiming to make music composition more accessible and personalized. This system represents a step towards integrating AI into the creative process, offering a new tool for composition support and collaborative artistic exploration.

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