Many-to-Many Singing Performance Style Transfer on Pitch and Energy Contours

Singing voice conversion (SVC) aims to convert the singer identity of a singing voice to that of another singer. However, most existing SVC systems only perform the conversion of timbre information, while leaving other information unchanged. This approach does not consider other aspects of singer identity, particularly a singer's performance style, which is reflected in the pitch (F0) and the energy (volume dynamics) contours of singing. To address this issue, this paper proposes a many-to-many singing performance style transfer system that converts the pitch and energy contours of one singer's style to another singer's. To achieve this target, we utilize two AutoVC-like autoencoders with an information bottleneck to automatically disentangle performance style from other musical contents, one for the pitch contour while another for the energy contour. Experiment results suggested that the proposed model can perform singing performance style transfer in a many-to-many conversion scenario, resulting in improved singer identity similarity to the target singer.

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Publication Details

Journal
IEEE Signal Processing Letters
Published
2024-11-25
DOI
https://doi.org/10.1109/lsp.2024.3506858
Primary Topic
Music and Audio Processing
Type
article
Field-Weighted Citation Impact
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article

Many-to-Many Singing Performance Style Transfer on Pitch and Energy Contours

Jun-You Wang, Jyh‐Shing Roger Jang, Yu-Teng Hsu
IEEE Signal Processing Letters
Music and Audio Processing
article

Many-to-Many Singing Performance Style Transfer on Pitch and Energy Contours

Jun-You Wang, Jyh‐Shing Roger Jang, Yu-Teng Hsu
article en

Abstract

Singing voice conversion (SVC) aims to convert the singer identity of a singing voice to that of another singer. However, most existing SVC systems only perform the conversion of timbre information, while leaving other information unchanged. This approach does not consider other aspects of singer identity, particularly a singer's performance style, which is reflected in the pitch (F0) and the energy (volume dynamics) contours of singing. To address this issue, this paper proposes a many-to-many singing performance style transfer system that converts the pitch and energy contours of one singer's style to another singer's. To achieve this target, we utilize two AutoVC-like autoencoders with an information bottleneck to automatically disentangle performance style from other musical contents, one for the pitch contour while another for the energy contour. Experiment results suggested that the proposed model can perform singing performance style transfer in a many-to-many conversion scenario, resulting in improved singer identity similarity to the target singer.

IEEE Signal Processing LettersVol. 32
National Taiwan University (TW), Institute of Information Science, Academia Sinica (TW)
Affordable and clean energy
Openalex Percentile: Top 77%
Music and Audio Processing
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