mlsanityData to 14 Oct 2026

VibE-SVC: Vibrato Extraction with High-frequency F0 Contour for Singing Voice Conversion

arXiv 2505.20794 ↗First posted 27 May 2025cs.SD cs.AI eess.AScited by 1

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Abstract (arXiv)

Controlling singing style is crucial for achieving an expressive and natural singing voice. Among the various style factors, vibrato plays a key role in conveying emotions and enhancing musical depth. However, modeling vibrato remains challenging due to its dynamic nature, making it difficult to control in singing voice conversion. To address this, we propose VibESVC, a controllable singing voice conversion model that explicitly extracts and manipulates vibrato using discrete wavelet transform. Unlike previous methods that model vibrato implicitly, our approach decomposes the F0 contour into frequency components, enabling precise transfer. This allows vibrato control for enhanced flexibility. Experimental results show that VibE-SVC effectively transforms singing styles while preserving speaker similarity. Both subjective and objective evaluations confirm high-quality conversion.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 21 of its 34 references that are in the map. First posted on arXiv 27 May 2025.

Builds on

21 of 34 references.

References · 21

  1. 2021HuBERT: Self-Supervised Speech Representation Learning by Masked Prediction of Hidden Unitscited by 2,342
  2. 2016WaveNet: A Generative Model for Raw Audiocited by 1,722
  3. 2020HiFi-GAN: Generative Adversarial Networks for Efficient and High Fidelity Speech Synthesiscited by 1,154
  4. 2016Least Squares Generative Adversarial Networkscited by 1,001
  5. 2022DPM-Solver++: Fast Solver for Guided Sampling of Diffusion Probabilistic Modelscited by 938
  6. 2020FastSpeech 2: Fast and High-Quality End-to-End Text to Speechcited by 717
  7. 2021Conditional Variational Autoencoder with Adversarial Learning for End-to-End Text-to-Speechcited by 561
  8. 2022BigVGAN: A Universal Neural Vocoder with Large-Scale Trainingcited by 251
  9. 2023MERT: Acoustic Music Understanding Model with Large-Scale Self-supervised Trainingcited by 181
  10. 2021DiffSinger: Singing Voice Synthesis via Shallow Diffusion Mechanismcited by 154
  11. 2021DiffSVC: A Diffusion Probabilistic Model for Singing Voice Conversioncited by 39
  12. 2021VISinger: Variational Inference with Adversarial Learning for End-to-End Singing Voice Synthesiscited by 38
9 more
  1. 2024TCSinger: Zero-Shot Singing Voice Synthesis with Style Transfer and Multi-Level Style Controlcited by 20
  2. 2019Singing Voice Conversion with Disentangled Representations of Singer and Vocal Technique Using Variational Autoencoderscited by 18
  3. 2019Unsupervised Singing Voice Conversioncited by 14
  4. 2021Towards High-fidelity Singing Voice Conversion with Acoustic Reference and Contrastive Predictive Codingcited by 8
  5. 2023VITS-Based Singing Voice Conversion Leveraging Whisper and multi-scale F0 Modelingcited by 6
  6. 2022Singing Voice Synthesis with Vibrato Modeling and Latent Energy Representationcited by 4
  7. 2024SPA-SVC: Self-supervised Pitch Augmentation for Singing Voice Conversioncited by 3
  8. 2024Period Singer: Integrating Periodic and Aperiodic Variational Autoencoders for Natural-Sounding End-to-End Singing Voice Synthesiscited by 3
  9. 2021Boosting the Predictive Accurary of Singer Identification Using Discrete Wavelet Transform For Feature Extractioncited by 1

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2026: 1.

1 paper.

  1. 2026Vibrato Expression Control for Singing Voice Conversion with Improving Independent Controlcited by 0