Closing the Loop: Enabling User Feedback and Testing in Symbolic Music Generation through a Python Framework and Ableton Live Integration

https://aimc2023.pubpub.org/pub/9pokd9f8

Symbolic music generation systems have seen rapid advancements, encompassing various techniques such as harmonization, text-to-music, and music infilling. However, most of these systems lack a corresponding user interface, limiting accessibility and hindering potential applications for composers and AI tool users. This paper proposes a python framework and an Ableton Live plugin designed to bridge the gap between deep learning researchers and user interest in these tools. The python framework provides APIs for seamless communication with the Ableton Live plugin, and the model can call those API to with their model’s specific functions. The Ableton Live plugin enables user interaction through its interface, allowing parameter configuration and control over the generation process. By facilitating testing and user interaction, this framework aims to enhance collaboration and accelerate advancements in the field of symbolic music generation.