Artificial intelligence has penetrated deeply into the domain of music creation, with tools offering myriad functionalities for various user demographics. Researchers led by Yueyue Zhu sought to evaluate these AI music generation tools comprehensively. Their research classified the tools into three groups: parameter-based, text-based, and visual-based, each catering to a different aspect of the music creation process.

• Comprehensive survey separating tools into categories
• Evaluation of features suitable for both casual listeners and professionals
• Analysis of each tool’s advantages and limitations
• Insight into AI music generation’s mechanisms and challenges

The array of tools available and their diverse applications signify the rapid evolution of AI in music generation. Tailoring these tools to the needs of various users, from recreational to professional, showcases the technology’s adaptability and potential for future advancement.