JSSS: free Japanese speech corpus for summarization and simplification
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Abstract (arXiv)
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 speech synthesis from short-form sentences, we aim to design more difficult tasks for delivering information to humans. Our corpus contains voices recorded for two tasks that have a role in providing information under constraints: duration-constrained text-to-speech summarization and speaking-style simplification. It also contains utterances of long-form sentences as an optional task. This paper describes how we designed the corpus, which is available on our project page.
Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). First posted on arXiv 5 Oct 2020.
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Citing papers per year: 2024: 1; 2025: 1; 2026: 1.
3 papers.
- 2024Analytic Study of Text-Free Speech Synthesis for Raw Audio using a Self-Supervised Learning Modelcited by 1
- 2026Alethia: A Foundational Encoder for Voice Deepfakescited by 1
- 2025MixedG2P-T5: G2P-free Speech Synthesis for Mixed-script texts using Speech Self-Supervised Learning and Language Modelcited by 0
- 2026Alethia: A Foundational Encoder for Voice Deepfakes30 Apr 2026
- 2025MixedG2P-T5: G2P-free Speech Synthesis for Mixed-script texts using Speech Self-Supervised Learning and Language Model1 Sep 2025
- 2024Analytic Study of Text-Free Speech Synthesis for Raw Audio using a Self-Supervised Learning Model4 Dec 2024