  There is an increasing interest from ML and HCI communities in empowering
creators with better generative models and more intuitive interfaces with which
to control them. In music, ML researchers have focused on training models
capable of generating pieces with increasing long-range structure and musical
coherence, while HCI researchers have separately focused on designing steering
interfaces that support user control and ownership. In this study, we
investigate through a common framework how developments in both models and user
interfaces are important for empowering co-creation where the goal is to create
music that communicates particular imagery or ideas (e.g., as is common for
other purposeful tasks in music creation like establishing mood or creating
accompanying music for another media). Our study is distinguished in that it
measures communication through both composer's self-reported experiences, and
how listeners evaluate this communication through the music. In an evaluation
study with 26 composers creating 100+ pieces of music and listeners providing
1000+ head-to-head comparisons, we find that more expressive models and more
steerable interfaces are important and complementary ways to make a difference
in composers communicating through music and supporting their creative
empowerment.
