  Text-to-motion diffusion models can generate realistic animations from text
prompts, but do not support fine-grained motion editing controls. In this
paper, we present a method for using natural language to iteratively specify
local edits to existing character animations, a task that is common in most
computer animation workflows. Our key idea is to represent a space of motion
edits using a set of kinematic motion editing operators (MEOs) whose effects on
the source motion is well-aligned with user expectations. We provide an
algorithm that leverages pre-existing language models to translate textual
descriptions of motion edits into source code for programs that define and
execute sequences of MEOs on a source animation. We execute MEOs by first
translating them into keyframe constraints, and then use diffusion-based motion
models to generate output motions that respect these constraints. Through a
user study and quantitative evaluation, we demonstrate that our system can
perform motion edits that respect the animator's editing intent, remain
faithful to the original animation (it edits the original animation, but does
not dramatically change it), and yield realistic character animation results.
