Report PPT:<File>
TOPIC
“Novice-AI Music Co-Creation via
AI-Steering Tools for Deep Generative Models “
Authors: Ryan Louie∗, Andy Coenen†, Cheng Zhi Huang, Michael Terry†, Carrie J. Cai†
<Publication:ACM SIGCHI 2020, April 25–30, 2020, Honolulu, HI, USA> https://dl.acm.org/doi/10.1145/3313831.3376739
ABSTRACT
While generative deep neural networks (DNNs) have demonstrated
their capacity for creating novel musical compositions,
less attention has been paid to the challenges and potential of
co-creating with these musical AIs, especially for novices. In
a needfinding study with a widely used, interactive musical AI,
we found that the AI can overwhelm users with the amount of
musical content it generates, and frustrate them with its nondeterministic
output. To better match co-creation needs, we
developed AI-steering tools, consisting of Voice Lanes that restrict
content generation to particular voices; Example-Based
Sliders to control the similarity of generated content to an
existing example; Semantic Sliders to nudge music generation
in high-level directions (happy/sad, conventional/surprising);
and Multiple Alternatives of generated content to audition and
choose from. We discovered the
tools not only increased users’ trust, control, comprehension,
and sense of collaboration with the AI, but also contributed to
a greater sense of self-efficacy and ownership of the composition
relative to the AI.
