An interactive music infilling interface for pop music composition

TL;DR

This paper presents an interactive AI-powered music infilling interface for pop music composition, enabling musicians to generate and explore variations with adjustable control parameters, thus making AI tools more accessible and practical.

Contribution

It introduces a max patch interface with multiple control levels for music infilling, integrating cloud-based AI to assist musicians in real-time composition tasks.

Findings

Enables selection of specific tracks for infilling

Provides multiple variations of generated music

Facilitates interactive composition process

Abstract

Artificial intelligence (AI) has been widely applied to music generation topics such as continuation, melody/harmony generation, genre transfer and music infilling application. Although with the burst interest to apply AI to music, there are still few interfaces for the musicians to take advantage of the latest progress of the AI technology. This makes those tools less valuable in practice and harder to find its advantage/drawbacks without utilizing them in the real scenario. This work builds a max patch for interactive music infilling application with different levels of control, including track density/polyphony/occupation rate and bar tonal tension control. The user can select the melody/bass/harmony track as the infilling content up to 16 bars. The infilling algorithm is based on the author's previous work, and the interface sends/receives messages to the AI system hosted in the cloud. This interface lowers the barrier of AI technology and can generate different variations of the selected content. Those results can give several alternatives to the musicians' composition, and the interactive process realizes the value of the AI infilling system.