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

arXiv eess.ASby Wataru Nakata, Kentaro Seki, Hitomi Yanaka, Yuki Saito, Shinnosuke Takamichi, Hiroshi SaruwatariApril 3, 20261 min read1 views
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arXiv:2407.15828v2 Announce Type: replace-cross Abstract: Spoken dialogue is essential for human-AI interactions, providing expressive capabilities beyond text. Developing effective spoken dialogue systems (SDSs) requires large-scale, high-quality, and diverse spoken dialogue corpora. However, existing datasets are often limited in size, spontaneity, or linguistic coherence. To address these limitations, we introduce J-CHAT, a 76,000-hour open-source Japanese spoken dialogue corpus. Constructed using an automated, language-independent methodology, J-CHAT ensures acoustic cleanliness, diversity, and natural spontaneity. The corpus is built from YouTube and podcast data, with extensive filtering and denoising to enhance quality. Experimental results with generative spoken dialogue language m

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Abstract:Spoken dialogue is essential for human-AI interactions, providing expressive capabilities beyond text. Developing effective spoken dialogue systems (SDSs) requires large-scale, high-quality, and diverse spoken dialogue corpora. However, existing datasets are often limited in size, spontaneity, or linguistic coherence. To address these limitations, we introduce J-CHAT, a 76,000-hour open-source Japanese spoken dialogue corpus. Constructed using an automated, language-independent methodology, J-CHAT ensures acoustic cleanliness, diversity, and natural spontaneity. The corpus is built from YouTube and podcast data, with extensive filtering and denoising to enhance quality. Experimental results with generative spoken dialogue language models trained on J-CHAT demonstrate its effectiveness for SDS development. By providing a robust foundation for training advanced dialogue models, we anticipate that J-CHAT will drive progress in human-AI dialogue research and applications.

Comments: 8 pages, 3 figures

Subjects:

Computation and Language (cs.CL); Sound (cs.SD); Audio and Speech Processing (eess.AS)

Cite as: arXiv:2407.15828 [cs.CL]

(or arXiv:2407.15828v2 [cs.CL] for this version)

https://doi.org/10.48550/arXiv.2407.15828

arXiv-issued DOI via DataCite

Submission history

From: Wataru Nakata [view email] [v1] Mon, 22 Jul 2024 17:46:50 UTC (4,158 KB) [v2] Thu, 2 Apr 2026 09:29:59 UTC (396 KB)

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