  This paper shows that StarGAN-VC, a spectral envelope transformation method
for non-parallel many-to-many voice conversion (VC), is capable of emotional VC
(EVC). Although StarGAN-VC has been shown to enable speaker identity
conversion, its capability for EVC for Japanese phrases has not been clarified.
In this paper, we describe the direct application of StarGAN-VC to an EVC task
with minimal fundamental frequency and aperiodicity processing. Through
subjective evaluation experiments, we evaluated the performance of our
StarGAN-EVC system in terms of its ability to achieve EVC for Japanese phrases.
The subjective evaluation is conducted in terms of subjective classification
and mean opinion score of neutrality and similarity. In addition, the
interdependence between the source and target emotional domains was
investigated from the perspective of the quality of EVC.
