Skip to yearly menu bar Skip to main content

Workshop: Machine Learning for Audio

InstrumentGen: Generating Sample-Based Musical Instruments From Text

Shahan Nercessian · Johannes Imort


We introduce the text-to-instrument task, which aims at generating sample-based musical instruments based on textual prompts. We propose InstrumentGen, a model that extends a text-prompted generative audio framework to condition on instrument family, source type, pitch (across an 88-key spectrum), velocity, and a joint text/audio embedding. Furthermore, we present a differentiable loss function to evaluate the intra-instrument timbral consistency of sample-based instruments. Our results establish a foundational text-to-instrument baseline, extending research in the domain of automatic sample-based instrument generation.

Chat is not available.