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20172024
most citedJSUT corpus: free large-scale Japanese speech corpus for end-to-end speech synthesis

88 citations · 308 across the 88 of their papers we have counts for

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11 papers · 1 filter

eess.AS2024

DNN-based ensemble singing voice synthesis with interactions between singers

Hiroaki Hyodo, Shinnosuke Takamichi, Tomohiko Nakamura +2

We propose a singing voice synthesis (SVS) method for a more unified ensemble singing voice by modeling interactions between singers. Most existing SVS methods aim to synthesize a…

eess.AS2024

BigCodec: Pushing the Limits of Low-Bitrate Neural Speech Codec

Detai Xin, Xu Tan, Shinnosuke Takamichi +1

We present BigCodec, a low-bitrate neural speech codec. While recent neural speech codecs have shown impressive progress, their performance significantly deteriorates at low bitrat…

eess.AS2024

SaSLaW: Dialogue Speech Corpus with Audio-visual Egocentric Information Toward Environment-adaptive Dialogue Speech Synthesis

Osamu Take, Shinnosuke Takamichi, Kentaro Seki +2

This paper presents SaSLaW, a spontaneous dialogue speech corpus containing synchronous recordings of what speakers speak, listen to, and watch. Humans consider the diverse environ…

cs.CL2024

J-CHAT: Japanese Large-scale Spoken Dialogue Corpus for Spoken Dialogue Language Modeling

Wataru Nakata, Kentaro Seki, Hitomi Yanaka +3

Spoken dialogue is essential for human-AI interactions, providing expressive capabilities beyond text. Developing effective spoken dialogue systems (SDSs) requires large-scale, hig…

cs.SD2024

Spatial Voice Conversion: Voice Conversion Preserving Spatial Information and Non-target Signals

Kentaro Seki, Shinnosuke Takamichi, Norihiro Takamune +3

This paper proposes a new task called spatial voice conversion, which aims to convert a target voice while preserving spatial information and non-target signals. Traditional voice…

cs.SD2024

Noise-Robust Voice Conversion by Conditional Denoising Training Using Latent Variables of Recording Quality and Environment

Takuto Igarashi, Yuki Saito, Kentaro Seki +4

We propose noise-robust voice conversion (VC) which takes into account the recording quality and environment of noisy source speech. Conventional denoising training improves the no…