  Photo applications offer tools for annotation via text and stickers.
Ideophones, mimetic and onomatopoeic words, which are common in graphic novels,
have yet to be explored for photo annotation use. We present a method for
automatic ideophone recommendation and positioning of the text on photos. These
annotations are accomplished by obtaining a list of ideophones with English
definitions and applying a suite of visual object detectors to the image. Next,
a semantic embedding maps the visual objects to the possible relevant
ideophones. Our system stands in contrast to traditional computer vision-based
annotation systems, which stop at recommending object and scene-level
annotation, by providing annotations that are communicative, fun, and engaging.
We test these annotations in Japanese and find they carry a strong preference
and increase enjoyment and sharing likelihood when compared to unannotated and
object-based annotated photos.
