mlsanityData to 14 Oct 2026

JSUT corpus: free large-scale Japanese speech corpus for end-to-end speech synthesis

arXiv 1711.00354 ↗First posted 28 Oct 2017cs.CLcited by 58

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Abstract (arXiv)

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 companies has an important role. However, such a corpus for Japanese speech synthesis does not exist. In this paper, we designed a novel Japanese speech corpus, named the "JSUT corpus," that is aimed at achieving end-to-end speech synthesis. The corpus consists of 10 hours of reading-style speech data and its transcription and covers all of the main pronunciations of daily-use Japanese characters. In this paper, we describe how we designed and analyzed the corpus. The corpus is freely available online.

Key facts. Cited by 58 papers in the map (data through 14 Oct 2026). First posted on arXiv 28 Oct 2017.

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Citing papers per year: 2021: 6; 2022: 8; 2023: 9; 2024: 13; 2025: 14; 2026: 8.

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  1. 2021A Survey on Neural Speech Synthesiscited by 184
  2. 2021WaveFake: A Data Set to Facilitate Audio Deepfake Detectioncited by 78
  3. 2021ESPnet2-TTS: Extending the Edge of TTS Researchcited by 22
  4. 2022Controllable Data Generation by Deep Learning: A Reviewcited by 20
  5. 2024DFADD: The Diffusion and Flow-Matching Based Audio Deepfake Datasetcited by 20
  6. 2022Talking Face Generation with Multilingual TTScited by 18
  7. 2023Adapting Multilingual Speech Representation Model for a New, Underresourced Language through Multilingual Fine-tuning and Continued Pretrainingcited by 18
  8. 2023A Comparative Study on E-Branchformer vs Conformer in Speech Recognition, Translation, and Understanding Taskscited by 14
  9. 2023Integrating Pre-Trained Speech and Language Models for End-to-End Speech Recognitioncited by 10
  10. 2025Towards Interactive Intelligence for Digital Humanscited by 10
  11. 2022Attack Agnostic Dataset: Towards Generalization and Stabilization of Audio DeepFake Detectioncited by 9
  12. 2022SpecRNet: Towards Faster and More Accessible Audio DeepFake Detectioncited by 9
38 more
  1. 2023Multi-Dataset Co-Training with Sharpness-Aware Optimization for Audio Anti-spoofingcited by 9
  2. 2025LiteASR: Efficient Automatic Speech Recognition with Low-Rank Approximationcited by 7
  3. 2024The DeepSpeak Datasetcited by 6
  4. 2021RefineGAN: Universally Generating Waveform Better than Ground Truth with Highly Accurate Pitch and Intensity Responsescited by 5
  5. 2024InterBiasing: Boost Unseen Word Recognition through Biasing Intermediate Predictionscited by 5
  6. 2024SaMoye: Zero-shot Singing Voice Conversion Model Based on Feature Disentanglement and Enhancementcited by 5
  7. 2024VoiceWukong: Benchmarking Deepfake Voice Detectioncited by 5
  8. 2025MOLE: Metadata Extraction and Validation in Scientific Papers Using LLMscited by 5
  9. 2021Decoupling Speaker-Independent Emotions for Voice Conversion Via Source-Filter Networkscited by 4
  10. 2023Unsupervised Data Selection for TTS: Using Arabic Broadcast News as a Case Studycited by 4
  11. 2023Wave-U-Net Discriminator: Fast and Lightweight Discriminator for Generative Adversarial Network-Based Speech Synthesiscited by 4
  12. 2023Exploration of Language Dependency for Japanese Self-Supervised Speech Representation Modelscited by 4
  13. 2025Voice Cloning: Comprehensive Surveycited by 4
  14. 2025LLM-based Generative Error Correction for Rare Words with Synthetic Data and Phonetic Contextcited by 4
  15. 2021Towards Natural and Controllable Cross-Lingual Voice Conversion Based on Neural TTS Model and Phonetic Posteriorgramcited by 3
  16. 2024Lightweight Model Attribution and Detection of Synthetic Speech via Audio Residual Fingerprintscited by 3
  17. 2025WCTC-Biasing: Retraining-free Contextual Biasing ASR with Wildcard CTC-based Keyword Spotting and Inter-layer Biasingcited by 3
  18. 2026Sarashina2.2-TTS: Tackling Kanji Polyphony in Japanese Speech Generation via Data Scaling and Targeted Data Synthesiscited by 3
  19. 2022Investigation of Japanese PnG BERT language model in text-to-speech synthesis for pitch accent languagecited by 2
  20. 2023A Comparative Study of Voice Conversion Models with Large-Scale Speech and Singing Data: The T13 Systems for the Singing Voice Conversion Challenge 2023cited by 2
  21. 2024A Pilot Study of GSLM-based Simulation of Foreign Accentuation Only Using Native Speech Corporacited by 2
  22. 2025SupertonicTTS: Towards Highly Efficient and Streamlined Text-to-Speech Systemcited by 2
  23. 2025Re-evaluating Minimum Bayes Risk Decoding for Automatic Speech Recognitioncited by 2
  24. 2022Few-Shot Cross-Lingual TTS Using Transferable Phoneme Embeddingcited by 1
  25. 2024NAIST Simultaneous Speech Translation System for IWSLT 2024cited by 1
  26. 2024Analytic Study of Text-Free Speech Synthesis for Raw Audio using a Self-Supervised Learning Modelcited by 1
  27. 2024Efficient Adaptation of Multilingual Models for Japanese ASRcited by 1
  28. 2025XMAD-Bench: Cross-Domain Multilingual Audio Deepfake Benchmarkcited by 1
  29. 2025Transcript-Prompted Whisper with Dictionary-Enhanced Decoding for Japanese Speech Annotationcited by 1
  30. 2025UtterTune: LoRA-Based Target-Language Pronunciation Edit and Control in Multilingual Text-to-Speechcited by 1
  31. 2025Building Tailored Speech Recognizers for Japanese Speaking Assessmentcited by 1
  32. 2025Multi-Accent Mandarin Dry-Vocal Singing Dataset: Benchmark for Singing Accent Recognitioncited by 1
  33. 2026Alethia: A Foundational Encoder for Voice Deepfakescited by 1
  34. 2022Dict-TTS: Learning to Pronounce with Prior Dictionary Knowledge for Text-to-Speechcited by 0
  35. 2022Empirical Study Incorporating Linguistic Knowledge on Filled Pauses for Personalized Spontaneous Speech Synthesiscited by 0
  36. 2023Automatic Tuning of Loss Trade-offs without Hyper-parameter Search in End-to-End Zero-Shot Speech Synthesiscited by 0
  37. 2024Maximizing Data Efficiency for Cross-Lingual TTS Adaptation by Self-Supervised Representation Mixing and Embedding Initializationcited by 0
  38. 2024A quest through interconnected datasets: lessons from highly-cited ICASSP paperscited by 0

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