Zixuan Feng1 and Edmond You2, 1USA, 2California State Polytechnic University, USA
This research paper explores the development of an intelligent music generation application designed to overcome creative stagnation in the music composition process [1]. The app leverages advanced AI techniques, specifically an improved Transformer-XL model, to generate original music based on user inputs, such as text prompts or audio files [2]. The system integrates three major components: a user-friendly interface built with Flutter, a robust backend powered by Python and Firebase for data management, and an AI engine for music generation [3]. Through experiments, the app's performance was evaluated in terms of quality and latency across different input complexities. Results showed that while the AI performs well with simple inputs, it faces challenges with more complex or abstract data, highlighting areas for further optimization. The project demonstrates significant potential in democratizing music creation, providing musicians with an accessible tool to generate and refine musical ideas, ultimately enhancing productivity and creativity in the music industry [3].
AI-driven music generation, Flutter, Music composition, Algorithmic composition, Music technology
