mlsanityData to 7 Oct 2026

FLEURS-R: A Restored Multilingual Speech Corpus for Generation Tasks

arXiv 2408.06227 ↗First posted 12 Aug 2024cs.CL cs.AI cs.SDcited by 13

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Abstract (arXiv)

This paper introduces FLEURS-R, a speech restoration applied version of the Few-shot Learning Evaluation of Universal Representations of Speech (FLEURS) corpus. FLEURS-R maintains an N-way parallel speech corpus in 102 languages as FLEURS, with improved audio quality and fidelity by applying the speech restoration model Miipher. The aim of FLEURS-R is to advance speech technology in more languages and catalyze research including text-to-speech (TTS) and other speech generation tasks in low-resource languages. Comprehensive evaluations with the restored speech and TTS baseline models trained from the new corpus show that the new corpus obtained significantly improved speech quality while maintaining the semantic contents of the speech. The corpus is publicly released via Hugging Face.

Key facts. Cited by 13 papers in the map (data through 7 Oct 2026). Builds on 27 of its 30 references that are in the map. First posted on arXiv 12 Aug 2024.

Builds on

27 of 30 references.

References · 27

  1. 2020Conformer: Convolution-augmented Transformer for Speech Recognitioncited by 1,838
  2. 2021SoundStream: An End-to-End Neural Audio Codeccited by 756
  3. 2023Neural Codec Language Models are Zero-Shot Text to Speech Synthesizerscited by 737
  4. 2022High Fidelity Neural Audio Compressioncited by 673
  5. 2019LibriTTS: A Corpus Derived from LibriSpeech for Text-to-Speechcited by 639
  6. 2020WaveGrad: Estimating Gradients for Waveform Generationcited by 620
  7. 2022AudioLM: a Language Modeling Approach to Audio Generationcited by 611
  8. 2020MLS: A Large-Scale Multilingual Dataset for Speech Researchcited by 467
  9. 2022FLEURS: Few-shot Learning Evaluation of Universal Representations of Speechcited by 458
  10. 2021Grad-TTS: A Diffusion Probabilistic Model for Text-to-Speechcited by 445
  11. 2021W2v-BERT: Combining Contrastive Learning and Masked Language Modeling for Self-Supervised Speech Pre-Trainingcited by 340
  12. 2023AudioPaLM: A Large Language Model That Can Speak and Listencited by 333
15 more
  1. 2021Layer-wise Analysis of a Self-supervised Speech Representation Modelcited by 293
  2. 2021YourTTS: Towards Zero-Shot Multi-Speaker TTS and Zero-Shot Voice Conversion for everyonecited by 277
  3. 2023Google USM: Scaling Automatic Speech Recognition Beyond 100 Languagescited by 228
  4. 2023Speak, Read and Prompt: High-Fidelity Text-to-Speech with Minimal Supervisioncited by 167
  5. 2022PromptTTS: Controllable Text-to-Speech with Text Descriptionscited by 106
  6. 2023LibriTTS-R: A Restored Multi-Speaker Text-to-Speech Corpuscited by 100
  7. 2023InstructTTS: Modelling Expressive TTS in Discrete Latent Space with Natural Language Style Promptcited by 90
  8. 2021PnG BERT: Augmented BERT on Phonemes and Graphemes for Neural TTScited by 52
  9. 2022WaveFit: An Iterative and Non-autoregressive Neural Vocoder based on Fixed-Point Iterationcited by 20
  10. 2021DF-Conformer: Integrated architecture of Conv-TasNet and Conformer using linear complexity self-attention for speech enhancementcited by 16
  11. 2023CML-TTS A Multilingual Dataset for Speech Synthesis in Low-Resource Languagescited by 15
  12. 2022Maestro-U: Leveraging joint speech-text representation learning for zero supervised speech ASRcited by 13
  13. 2022SQuId: Measuring Speech Naturalness in Many Languagescited by 10
  14. 2024Extending Multilingual Speech Synthesis to 100+ Languages without Transcribed Datacited by 9
  15. 2022Attentive Temporal Pooling for Conformer-based Streaming Language Identification in Long-form Speechcited by 6

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 2; 2025: 5; 2026: 6.

13 papers.

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