88 citations · 308 across the 88 of their papers we have counts for
4 papers · 1 filter
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…
Do learned speech symbols follow Zipf's law?
Shinnosuke Takamichi, Hiroki Maeda, Joonyong Park +2
In this study, we investigate whether speech symbols, learned through deep learning, follow Zipf's law, akin to natural language symbols. Zipf's law is an empirical law that deline…
How Generative Spoken Language Modeling Encodes Noisy Speech: Investigation from Phonetics to Syntactics
Joonyong Park, Shinnosuke Takamichi, Tomohiko Nakamura +3
We examine the speech modeling potential of generative spoken language modeling (GSLM), which involves using learned symbols derived from data rather than phonemes for speech analy…
JSUT corpus: free large-scale Japanese speech corpus for end-to-end speech synthesis
Ryosuke Sonobe, Shinnosuke Takamichi, Hiroshi Saruwatari
Thanks to improvements in machine learning techniques including deep learning, a free large-scale speech corpus that can be shared between academic institutions and commercial comp…