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JSSS: free Japanese speech corpus for summarization and simplification

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arxiv 2010.01793 v1 pith:F55EEP7A submitted 2020-10-05 eess.AS cs.SD

Shinnosuke Takamichi , Mamoru Komachi , Naoko Tanji , Hiroshi Saruwatari This is my paper · ORCID
classification eess.AScs.SD
keywords corpussimplificationspeechsummarizationcontainsinformationjapanesejsss
verification ladder T0 review T1 audit T2 compute T3 formal
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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.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. MixedG2P-T5: G2P-free Speech Synthesis for Mixed-script texts using Speech Self-Supervised Learning and Language Model

    eess.AS 2025-09 conditional novelty 5.0 of 10

    A T5 model predicts SSL-derived discrete speech tokens directly from mixed-script Japanese text, letting a FastSpeech 2 synthesizer produce speech without a grapheme-to-phoneme module.

  2. Analytic Study of Text-Free Speech Synthesis for Raw Audio using a Self-Supervised Learning Model

    cs.CL 2024-12 conditional novelty 4.0 of 10

    SSL discrete tokens outperform ASR transcripts on naturalness and acoustic quality, but not intelligibility, in a two-language comparison of text-free TTS.

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