  We propose a method for synthesizing environmental sounds from visually
represented onomatopoeias and sound sources. An onomatopoeia is a word that
imitates a sound structure, i.e., the text representation of sound. From this
perspective, onoma-to-wave has been proposed to synthesize environmental sounds
from the desired onomatopoeia texts. Onomatopoeias have another representation:
visual-text representations of sounds in comics, advertisements, and virtual
reality. A visual onomatopoeia (visual text of onomatopoeia) contains rich
information that is not present in the text, such as a long-short duration of
the image, so the use of this representation is expected to synthesize diverse
sounds. Therefore, we propose visual onoma-to-wave for environmental sound
synthesis from visual onomatopoeia. The method can transfer visual concepts of
the visual text and sound-source image to the synthesized sound. We also
propose a data augmentation method focusing on the repetition of onomatopoeias
to enhance the performance of our method. An experimental evaluation shows that
the methods can synthesize diverse environmental sounds from visual text and
sound-source images.
