Score and Lyrics-Free Singing Voice Generation
Not on the map. Why?
Abstract (arXiv)
Generative models for singing voice have been mostly concerned with the task of ``singing voice synthesis,'' i.e., to produce singing voice waveforms given musical scores and text lyrics. In this work, we explore a novel yet challenging alternative: singing voice generation without pre-assigned scores and lyrics, in both training and inference time. In particular, we outline three such generation schemes, and propose a pipeline to tackle these new tasks. Moreover, we implement such models using generative adversarial networks and evaluate them both objectively and subjectively.
Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). First posted on arXiv 26 Dec 2019.
Builds on
No reference list yet.
Built on by
Citing papers per year: 2021: 1; 2022: 1; 2023: 1; 2024: 0; 2025: 1.
4 papers.
- 2023The Ethical Implications of Generative Audio Models: A Systematic Literature Reviewcited by 18
- 2021KaraSinger: Score-Free Singing Voice Synthesis with VQ-VAE using Mel-spectrogramscited by 3
- 2022SingAug: Data Augmentation for Singing Voice Synthesis with Cycle-consistent Training Strategycited by 3
- 2025Mamba2 Meets Silence: Robust Vocal Source Separation for Sparse Regionscited by 0
- 2025Mamba2 Meets Silence: Robust Vocal Source Separation for Sparse Regions20 Aug 2025
- 2023The Ethical Implications of Generative Audio Models: A Systematic Literature Review7 Jul 2023
- 2022SingAug: Data Augmentation for Singing Voice Synthesis with Cycle-consistent Training Strategy31 Mar 2022
- 2021KaraSinger: Score-Free Singing Voice Synthesis with VQ-VAE using Mel-spectrograms8 Oct 2021