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

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arxiv 2306.15412 v2 pith:3UMXOKQB submitted 2023-06-27 cs.SD eess.AS

Haojie Wei , Xueke Cao , Tangpeng Dan , Yueguo Chen This is my paper · ORCID
classification cs.SDeess.AS
keywords musicvocalrmvpepitchpolyphonicmodelpitchesrobust
verification ladder T0 review T1 audit T2 compute T3 formal

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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.

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Forward citations

Cited by 7 Pith papers

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