# GTSinger: A Global Multi-Technique Singing Corpus with Realistic Music Scores for All Singing Tasks

arXiv: https://arxiv.org/abs/2409.13832 · HTML: https://mlsanity.com/paper/2409.13832/

## Key facts

- Cited by 30 papers in the map (data through 14 Oct 2026).
- Builds on 18 of its 35 references that are in the map.
- First posted on arXiv 20 Sep 2024.

## Builds on (most cited first, 18 of 18)

- [WavLM: Large-Scale Self-Supervised Pre-Training for Full Stack Speech Processing](https://mlsanity.com/paper/2110.13900/) (2021)
- [HiFi-GAN: Generative Adversarial Networks for Efficient and High Fidelity Speech Synthesis](https://mlsanity.com/paper/2010.05646/) (2020)
- [DiffSinger: Singing Voice Synthesis via Shallow Diffusion Mechanism](https://mlsanity.com/paper/2105.02446/) (2021)
- [Multi-Singer: Fast Multi-Singer Singing Voice Vocoder With A Large-Scale Corpus](https://mlsanity.com/paper/2112.10358/) (2021)
- [SingSong: Generating musical accompaniments from singing](https://mlsanity.com/paper/2301.12662/) (2023)
- [Opencpop: A High-Quality Open Source Chinese Popular Song Corpus for Singing Voice Synthesis](https://mlsanity.com/paper/2201.07429/) (2022)
- [VISinger: Variational Inference with Adversarial Learning for End-to-End Singing Voice Synthesis](https://mlsanity.com/paper/2110.08813/) (2021)
- [RMVPE: A Robust Model for Vocal Pitch Estimation in Polyphonic Music](https://mlsanity.com/paper/2306.15412/) (2023)
- [StyleSinger: Style Transfer for Out-of-Domain Singing Voice Synthesis](https://mlsanity.com/paper/2312.10741/) (2023)
- [NHSS: A Speech and Singing Parallel Database](https://mlsanity.com/paper/2012.00337/) (2020)
- [JVS-MuSiC: Japanese multispeaker singing-voice corpus](https://mlsanity.com/paper/2001.07044/) (2020)
- [RMSSinger: Realistic-Music-Score based Singing Voice Synthesis](https://mlsanity.com/paper/2305.10686/) (2023)
- [Learning the Beauty in Songs: Neural Singing Voice Beautifier](https://mlsanity.com/paper/2202.13277/) (2022)
- [Self-Supervised Representations for Singing Voice Conversion](https://mlsanity.com/paper/2303.12197/) (2023)
- [WeSinger: Data-augmented Singing Voice Synthesis with Auxiliary Losses](https://mlsanity.com/paper/2203.10750/) (2022)
- [MuSE-SVS: Multi-Singer Emotional Singing Voice Synthesizer that Controls Emotional Intensity](https://mlsanity.com/paper/2203.00931/) (2022)
- [Robust One-Shot Singing Voice Conversion](https://mlsanity.com/paper/2210.11096/) (2022)
- [AlignSTS: Speech-to-Singing Conversion via Cross-Modal Alignment](https://mlsanity.com/paper/2305.04476/) (2023)

## Built on by (most cited first, 30 of 30)

- [AV-Odyssey Bench: Can Your Multimodal LLMs Really Understand Audio-Visual Information?](https://mlsanity.com/paper/2412.02611/) (2024)
- [TCSinger: Zero-Shot Singing Voice Synthesis with Style Transfer and Multi-Level Style Control](https://mlsanity.com/paper/2409.15977/) (2024)
- [GRE Suite: Geo-localization Inference via Fine-Tuned Vision-Language Models and Enhanced Reasoning Chains](https://mlsanity.com/paper/2505.18700/) (2025)
- [SingMOS-Pro: An Comprehensive Benchmark for Singing Quality Assessment](https://mlsanity.com/paper/2510.01812/) (2025)
- [TCSinger 2: Customizable Multilingual Zero-shot Singing Voice Synthesis](https://mlsanity.com/paper/2505.14910/) (2025)
- [Vevo2: A Unified and Controllable Framework for Speech and Singing Voice Generation](https://mlsanity.com/paper/2508.16332/) (2025)
- [SongPrep: A Preprocessing Framework and End-to-end Model for Full-song Structure Parsing and Lyrics Transcription](https://mlsanity.com/paper/2509.17404/) (2025)
- [YingMusic-Singer: Zero-shot Singing Voice Synthesis and Editing with Annotation-free Melody Guidance](https://mlsanity.com/paper/2512.04779/) (2025)
- [Versatile Framework for Song Generation with Prompt-based Control](https://mlsanity.com/paper/2504.19062/) (2025)
- [Conan: A Chunkwise Online Network for Zero-Shot Adaptive Voice Conversion](https://mlsanity.com/paper/2507.14534/) (2025)
- [DiTSinger: Scaling Singing Voice Synthesis with Diffusion Transformer and Implicit Alignment](https://mlsanity.com/paper/2510.09016/) (2025)
- [YingMusic-SVC: Real-World Robust Zero-Shot Singing Voice Conversion with Flow-GRPO and Singing-Specific Inductive Biases](https://mlsanity.com/paper/2512.04793/) (2025)
- [SoulX-Singer: Towards High-Quality Zero-Shot Singing Voice Synthesis](https://mlsanity.com/paper/2602.07803/) (2026)
- [WavAlign: Enhancing Intelligence and Expressiveness in Spoken Dialogue Models via Adaptive Hybrid Post-Training](https://mlsanity.com/paper/2604.14932/) (2026)
- [Sylber 2.0: A Universal Syllable Embedding](https://mlsanity.com/paper/2601.22306/) (2026)
- [Controllable Singing Voice Synthesis using Phoneme-Level Energy Sequence](https://mlsanity.com/paper/2509.07038/) (2025)
- [R2-SVC: Towards Real-World Robust and Expressive Zero-shot Singing Voice Conversion](https://mlsanity.com/paper/2510.20677/) (2025)
- [Dual-Axis Generative Reward Model Toward Semantic and Turn-taking Robustness in Interactive Spoken Dialogue Models](https://mlsanity.com/paper/2604.14920/) (2026)
- [Towards Streaming Synchronized Spatial Audio Generation via Autoregressive Diffusion Transformer](https://mlsanity.com/paper/2605.30940/) (2026)
- [Leveraging Pretrained Diffusion Models for Zero-Shot Part Assembly](https://mlsanity.com/paper/2505.00426/) (2025)
- [SLEEPING-DISCO 9M: A large-scale pre-training dataset for generative music modeling](https://mlsanity.com/paper/2506.14293/) (2025)
- [SDiaReward: Modeling and Benchmarking Spoken Dialogue Rewards with Modality and Colloquialness](https://mlsanity.com/paper/2603.14889/) (2026)
- [Controllable Singing Style Conversion with Boundary-Aware Information Bottleneck](https://mlsanity.com/paper/2604.05526/) (2026)
- [VocalParse: Towards Unified and Scalable Singing Voice Transcription with Large Audio Language Models](https://mlsanity.com/paper/2605.04613/) (2026)
- [Vibrato Expression Control for Singing Voice Conversion with Improving Independent Control](https://mlsanity.com/paper/2606.17126/) (2026)
- [MPEcho: A Melody and Phoneme-Aware Generative Framework for Controllable Cover Song Generation](https://mlsanity.com/paper/2607.26698/) (2026)
- [VocalRender: Score-Native Singing Voice Synthesis for Real-World Composition](https://mlsanity.com/paper/2607.27768/) (2026)
- [CookVoice: Unified Framework for Style Controllable Multi-Modal Human Voice Generation](https://mlsanity.com/paper/2608.11590/) (2026)
- [Vocal Music under Phoneme-Conditional Analysis](https://mlsanity.com/paper/2608.30823/) (2026)
- [Gugak-VocalSet: A Multi-Genre Studio-Quality Dataset of Korean Traditional Singing with Sigimsae Annotations](https://mlsanity.com/paper/2610.15350/) (2026)

## Abstract (arXiv)

The scarcity of high-quality and multi-task singing datasets significantly hinders the development of diverse controllable and personalized singing tasks, as existing singing datasets suffer from low quality, limited diversity of languages and singers, absence of multi-technique information and realistic music scores, and poor task suitability. To tackle these problems, we present GTSinger, a large global, multi-technique, free-to-use, high-quality singing corpus with realistic music scores, designed for all singing tasks, along with its benchmarks. Particularly, (1) we collect 80.59 hours of high-quality singing voices, forming the largest recorded singing dataset; (2) 20 professional singers across nine widely spoken languages offer diverse timbres and styles; (3) we provide controlled comparison and phoneme-level annotations of six commonly used singing techniques, helping technique modeling and control; (4) GTSinger offers realistic music scores, assisting real-world musical composition; (5) singing voices are accompanied by manual phoneme-to-audio alignments, global style labels, and 16.16 hours of paired speech for various singing tasks. Moreover, to facilitate the use of GTSinger, we conduct four benchmark experiments: technique-controllable singing voice synthesis, technique recognition, style transfer, and speech-to-singing conversion. The demos can be found at http://aaronz345.github.io/GTSingerDemo/. We provide the dataset and the code for processing data and conducting benchmarks at https://huggingface.co/datasets/AaronZ345/GTSinger and https://github.com/AaronZ345/GTSinger.