mlsanityData to 7 Oct 2026

ASR data augmentation in low-resource settings using cross-lingual multi-speaker TTS and cross-lingual voice conversion

arXiv 2204.00618 ↗First posted 29 Mar 2022eess.AS cs.CL cs.SDcited by 10

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Abstract (arXiv)

We explore cross-lingual multi-speaker speech synthesis and cross-lingual voice conversion applied to data augmentation for automatic speech recognition (ASR) systems in low/medium-resource scenarios. Through extensive experiments, we show that our approach permits the application of speech synthesis and voice conversion to improve ASR systems using only one target-language speaker during model training. We also managed to close the gap between ASR models trained with synthesized versus human speech compared to other works that use many speakers. Finally, we show that it is possible to obtain promising ASR training results with our data augmentation method using only a single real speaker in a target language.

Key facts. Cited by 10 papers in the map (data through 7 Oct 2026). Builds on 27 of its 33 references that are in the map. First posted on arXiv 29 Mar 2022.

Builds on

27 of 33 references.

References · 27

  1. 2020wav2vec 2.0: A Framework for Self-Supervised Learning of Speech Representationscited by 3,853
  2. 2021WavLM: Large-Scale Self-Supervised Pre-Training for Full Stack Speech Processingcited by 1,609
  3. 2019Common Voice: A Massively-Multilingual Speech Corpuscited by 1,358
  4. 2017Natural TTS Synthesis by Conditioning WaveNet on Mel Spectrogram Predictionscited by 800
  5. 2019LibriTTS: A Corpus Derived from LibriSpeech for Text-to-Speechcited by 639
  6. 2021Conditional Variational Autoencoder with Adversarial Learning for End-to-End Text-to-Speechcited by 555
  7. 2020MLS: A Large-Scale Multilingual Dataset for Speech Researchcited by 467
  8. 2021VoxPopuli: A Large-Scale Multilingual Speech Corpus for Representation Learning, Semi-Supervised Learning and Interpretationcited by 455
  9. 2018Transfer Learning from Speaker Verification to Multispeaker Text-To-Speech Synthesiscited by 280
  10. 2021YourTTS: Towards Zero-Shot Multi-Speaker TTS and Zero-Shot Voice Conversion for everyonecited by 277
  11. 2020Glow-TTS: A Generative Flow for Text-to-Speech via Monotonic Alignment Searchcited by 269
  12. 2021The Multilingual TEDx Corpus for Speech Recognition and Translationcited by 101
15 more
  1. 2019QuartzNet: Deep Automatic Speech Recognition with 1D Time-Channel Separable Convolutionscited by 93
  2. 2021BigSSL: Exploring the Frontier of Large-Scale Semi-Supervised Learning for Automatic Speech Recognitioncited by 88
  3. 2020FullSubNet: A Full-Band and Sub-Band Fusion Model for Real-Time Single-Channel Speech Enhancementcited by 66
  4. 2019Speech Recognition with Augmented Synthesized Speechcited by 60
  5. 2019CSS10: A Collection of Single Speaker Speech Datasets for 10 Languagescited by 54
  6. 2020Flowtron: an Autoregressive Flow-based Generative Network for Text-to-Speech Synthesiscited by 54
  7. 2020Clova Baseline System for the VoxCeleb Speaker Recognition Challenge 2020cited by 36
  8. 2020You Do Not Need More Data: Improving End-To-End Speech Recognition by Text-To-Speech Data Augmentationcited by 29
  9. 2020Attentron: Few-Shot Text-to-Speech Utilizing Attention-Based Variable-Length Embeddingcited by 27
  10. 2018Training Neural Speech Recognition Systems with Synthetic Speech Augmentationcited by 21
  11. 2021Voice Conversion Can Improve ASR in Very Low-Resource Settingscited by 13
  12. 2018Machine Speech Chain with One-shot Speaker Adaptationcited by 11
  13. 2020Cross-Language Transfer Learning, Continuous Learning, and Domain Adaptation for End-to-End Automatic Speech Recognitioncited by 9
  14. 2020TTS-Portuguese Corpus: a corpus for speech synthesis in Brazilian Portuguesecited by 9
  15. 2021Brazilian Portuguese Speech Recognition Using Wav2vec 2.0cited by 6

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 3; 2025: 4; 2026: 3.

10 papers.

  1. 2024XTTS: a Massively Multilingual Zero-Shot Text-to-Speech Modelcited by 174
  2. 2025Data Quality Issues in Multilingual Speech Datasets: The Need for Sociolinguistic Awareness and Proactive Language Planningcited by 10
  3. 2024Generating Data with Text-to-Speech and Large-Language Models for Conversational Speech Recognitioncited by 9
  4. 2024Improving Accented Speech Recognition using Data Augmentation based on Unsupervised Text-to-Speech Synthesiscited by 5
  5. 2025An Exhaustive Evaluation of TTS- and VC-based Data Augmentation for ASRcited by 5
  6. 2025Towards Pretraining Robust ASR Foundation Model with Acoustic-Aware Data Augmentationcited by 1
  7. 2026Improving Code-Switching ASR with Code-Mixing Guided Synthetic Speechcited by 1
  8. 2025Voice Conversion Improves Cross-Domain Robustness for Spoken Arabic Dialect Identificationcited by 0
  9. 2026TASU2: Controllable CTC Simulation for Alignment and Low-Resource Adaptation of Speech LLMscited by 0
  10. 2026NOPE-HYPE: A Structured Simulation Workflow for Robust Speech-to-Text Across Diverse Acoustic Environmentscited by 0