  We present SRC4VC, a new corpus containing 11 hours of speech recorded on
smartphones by 100 Japanese speakers. Although high-quality multi-speaker
corpora can advance voice conversion (VC) technologies, they are not always
suitable for testing VC when low-quality speech recording is given as the
input. To this end, we first asked 100 crowdworkers to record their voice
samples using smartphones. Then, we annotated the recorded samples with
speaker-wise recording-quality scores and utterance-wise perceived emotion
labels. We also benchmark SRC4VC on any-to-any VC, in which we trained a
multi-speaker VC model on high-quality speech and used the SRC4VC speakers'
voice samples as the source in VC. The results show that the recording quality
mismatch between the training and evaluation data significantly degrades the VC
performance, which can be improved by applying speech enhancement to the
low-quality source speech samples.
