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Thanks to improvements in machine learning techniques, including deeplearning, speech synthesis is becoming a machine learning task. To acceleratespeech synthesis research, we are developing Japanese voice corpora reasonablyaccessible from not only academic institutions but also commercial companies.In 2017, we released the JSUT corpus, which contains 10 hours of reading-stylespeech uttered by a single speaker, for end-to-end text-to-speech synthesis.For more general use in speech synthesis research, e.g., voice conversion andmulti-speaker modeling, in this paper, we construct the JVS corpus, whichcontains voice data of 100 speakers in three styles (normal, whisper, andfalsetto). The corpus contains 30 hours of voice data including 22 hours ofparallel normal voices. This paper describes how we designed the corpus andsummarizes the specifications. The corpus is available at our project page.

JVS corpus: free Japanese multi-speaker voice corpus