  Synthesizing and converting environmental sounds have the potential for many
applications such as supporting movie and game production, data augmentation
for sound event detection and scene classification. Conventional works on
synthesizing and converting environmental sounds are based on a physical
modeling or concatenative approach. However, there are a limited number of
works that have addressed environmental sound synthesis and conversion with
statistical generative models; thus, this research area is not yet well
organized. In this paper, we review problem definitions, applications, and
evaluation methods of environmental sound synthesis and conversion. We then
report on environmental sound synthesis using sound event labels, in which we
focus on the current performance of statistical environmental sound synthesis
and investigate how we should conduct subjective experiments on environmental
sound synthesis.
