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.

中文翻译：

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JVS-MuSiC：日语多扬声器歌声语料库

由于机器学习技术的发展，合成单个歌手的高质量歌声已经成为可能。一个开放的多扬声器歌声语料库将进一步加速歌声合成的研究。然而，传统的歌声语料库仅由单个歌手的歌声组成。我们设计了一个名为“JVS-MuSiC”的日语多扬声器歌唱语音语料库，旨在分析和合成各种语音。该语料库由 100 位歌手录制的同一首歌 Katatsumuri 组成，这是一首日本儿童歌曲。它还包括另一首对每个歌手都不同的歌曲。在本文中，我们描述了使用 JVS-MuSiC 的语料库设计和实验分析。我们调查了1）歌声的相似性与同声歌声的感知统一性之间的关系，以及2）歌声与语音的相似性之间的关系。结果表明：1）歌声相似度与同音合一性之间存在正中度相关；2）歌声相似度与语音相似度之间的相关性较弱。该语料库可在线免费获取。