# RMVPE: A Robust Model for Vocal Pitch Estimation in Polyphonic Music

arXiv: https://arxiv.org/abs/2306.15412 · HTML: https://mlsanity.com/paper/2306.15412/

## Key facts

- Cited by 30 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 27 Jun 2023.

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

- [Zero-shot Voice Conversion with Diffusion Transformers](https://mlsanity.com/paper/2411.09943/) (2024)
- [GTSinger: A Global Multi-Technique Singing Corpus with Realistic Music Scores for All Singing Tasks](https://mlsanity.com/paper/2409.13832/) (2024)
- [FSD: An Initial Chinese Dataset for Fake Song Detection](https://mlsanity.com/paper/2309.02232/) (2023)
- [SaMoye: Zero-shot Singing Voice Conversion Model Based on Feature Disentanglement and Enhancement](https://mlsanity.com/paper/2407.07728/) (2024)
- [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)
- [RT-VC: Real-Time Zero-Shot Voice Conversion with Speech Articulatory Coding](https://mlsanity.com/paper/2506.10289/) (2025)
- [Pushing the Frontier of Full-Song Generation: Hierarchical Autoregressive Planning Meets Flow-Matching Rendering](https://mlsanity.com/paper/2607.20253/) (2026)
- [Low-latency Real-time Voice Conversion on CPU](https://mlsanity.com/paper/2311.00873/) (2023)
- [SPA-SVC: Self-supervised Pitch Augmentation for Singing Voice Conversion](https://mlsanity.com/paper/2406.05692/) (2024)
- [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)
- [FCPE: A Fast Context-based Pitch Estimation Model](https://mlsanity.com/paper/2509.15140/) (2025)
- [HQ-SVC: Towards High-Quality Zero-Shot Singing Voice Conversion in Low-Resource Scenarios](https://mlsanity.com/paper/2511.08496/) (2025)
- [AI Harmonizer: Expanding Vocal Expression with a Generative Neurosymbolic Music AI System](https://mlsanity.com/paper/2506.18143/) (2025)
- [ProMode: A Speech Prosody Model Conditioned on Acoustic and Textual Inputs](https://mlsanity.com/paper/2508.09389/) (2025)
- [Anonymization, Not Elimination: Utility-Preserved Speech Anonymization](https://mlsanity.com/paper/2604.17000/) (2026)
- [Word-wise intonation model for cross-language TTS systems](https://mlsanity.com/paper/2409.20374/) (2024)
- [MAJL: A Model-Agnostic Joint Learning Framework for Music Source Separation and Pitch Estimation](https://mlsanity.com/paper/2501.03689/) (2025)
- [Enhancing Speech Emotion Recognition with Graph-Based Multimodal Fusion and Prosodic Features for the Speech Emotion Recognition in Naturalistic Conditions Challenge at Interspeech 2025](https://mlsanity.com/paper/2506.02088/) (2025)
- [Controllable Singing Style Conversion with Boundary-Aware Information Bottleneck](https://mlsanity.com/paper/2604.05526/) (2026)
- [Vibrato Expression Control for Singing Voice Conversion with Improving Independent Control](https://mlsanity.com/paper/2606.17126/) (2026)
- [Pmeta-TLA: Backdoor Attacks for Speech Classification Models via Meta-Learning with Timbre Leakage Attack](https://mlsanity.com/paper/2607.01702/) (2026)
- [Unlocking Speech-Text Compositional Powers: Instruction-Following Speech Language Models without Instruction Tuning](https://mlsanity.com/paper/2607.02214/) (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)
- [Audio-to-Score Transcription using Pre-trained Features, Data Augmentation, and the New SheetSage-A2S Dataset](https://mlsanity.com/paper/2608.06165/) (2026)
- [Vocal Music under Phoneme-Conditional Analysis](https://mlsanity.com/paper/2608.30823/) (2026)
- [Open-Qwen-Music: An Auditable Framework for LLM-Based Music Composition and Diffusion Rendering](https://mlsanity.com/paper/2609.31652/) (2026)
- [Revisiting Input Time-frequency Representations in Multi-pitch Estimation for Vocal Ensembles](https://mlsanity.com/paper/2610.03656/) (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)

Vocal pitch is an important high-level feature in music audio processing. However, extracting vocal pitch in polyphonic music is more challenging due to the presence of accompaniment. To eliminate the influence of the accompaniment, most previous methods adopt music source separation models to obtain clean vocals from polyphonic music before predicting vocal pitches. As a result, the performance of vocal pitch estimation is affected by the music source separation models. To address this issue and directly extract vocal pitches from polyphonic music, we propose a robust model named RMVPE. This model can extract effective hidden features and accurately predict vocal pitches from polyphonic music. The experimental results demonstrate the superiority of RMVPE in terms of raw pitch accuracy (RPA) and raw chroma accuracy (RCA). Additionally, experiments conducted with different types of noise show that RMVPE is robust across all signal-to-noise ratio (SNR) levels. The code of RMVPE is available at https://github.com/Dream-High/RMVPE.