activity
20192022
most citedJVS corpus: free Japanese multi-speaker voice corpus

41 citations · 51 across the 6 of their papers we have counts for

collaborators

6 papers

eess.AS2022★ 8 cited

JaCappella Corpus: A Japanese a Cappella Vocal Ensemble Corpus

Tomohiko Nakamura, Shinnosuke Takamichi, Naoko Tanji +2

We construct a corpus of Japanese a cappella vocal ensembles (jaCappella corpus) for vocal ensemble separation and synthesis. It consists of 35 copyright-cleared vocal ensemble son…

cs.SD2022

SelfRemaster: Self-Supervised Speech Restoration with Analysis-by-Synthesis Approach Using Channel Modeling

Takaaki Saeki, Shinnosuke Takamichi, Tomohiko Nakamura +2

We present a self-supervised speech restoration method without paired speech corpora. Because the previous general speech restoration method uses artificial paired data created by…

cs.SD2022

J-MAC: Japanese multi-speaker audiobook corpus for speech synthesis

Shinnosuke Takamichi, Wataru Nakata, Naoko Tanji +1

In this paper, we construct a Japanese audiobook speech corpus called "J-MAC" for speech synthesis research. With the success of reading-style speech synthesis, the research target…

eess.AS2020

JSSS: free Japanese speech corpus for summarization and simplification

Shinnosuke Takamichi, Mamoru Komachi, Naoko Tanji +1

In this paper, we construct a new Japanese speech corpus for speech-based summarization and simplification, "JSSS" (pronounced "j-triple-s"). Given the success of reading-style spe…

cs.SD2020★ 2 cited

JVS-MuSiC: Japanese multispeaker singing-voice corpus

Hiroki Tamaru, Shinnosuke Takamichi, Naoko Tanji +1

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 corpu…

cs.SD2019★ 41 cited

JVS corpus: free Japanese multi-speaker voice corpus

Shinnosuke Takamichi, Kentaro Mitsui, Yuki Saito +3

Thanks to improvements in machine learning techniques, including deep learning, speech synthesis is becoming a machine learning task. To accelerate speech synthesis research, we ar…