  Thanks to developments in machine learning techniques, it has become possible
to synthesize high-quality singing voices of a single singer. An open
multispeaker singing-voice corpus would further accelerate the research in
singing-voice synthesis. However, conventional singing-voice corpora only
consist of the singing voices of a single singer. We designed a Japanese
multispeaker singing-voice corpus called "JVS-MuSiC" with the aim to analyze
and synthesize a variety of voices. The corpus consists of 100 singers'
recordings of the same song, Katatsumuri, which is a Japanese children's song.
It also includes another song that is different for each singer. In this paper,
we describe the design of the corpus and experimental analyses using JVS-MuSiC.
We investigated the relationship between 1) the similarity of singing voices
and perceptual oneness of unison singing voices and between 2) the similarity
of singing voices and that of speech. The results suggest that 1) there is a
positive and moderate correlation between singing-voice similarity and the
oneness of unison and that 2) the correlation between singing-voice similarity
and speech similarity is weak. This corpus is freely available online.
