Generative AI in Arabic Music: Composition and Innovation

This paper explores the power of artificial intelligence in the generation of Arabic music, a domain where traditional musical complexity meets modern computational techniques. It focuses on pulling Long Short-Term Memory (LSTM) networks and Convolutional Neural Networks (CNNs) to model and generate music sequences that maintain the distinctive qualities of traditional Arabic compositions. Utilizing a unique dataset of MIDI files from iconic Arabic songs, the study aims to demonstrate the capabilities of AI in understanding and reproducing the complex patterns of Arabic music. This research not only contributes to the academic field by filling the gap in studies concerning Arabic music generation but also enhances practical applications by providing tools that enable non-experts to produce music autonomously.