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Computer Science > Sound

arXiv:2501.02953 (cs)
[Submitted on 6 Jan 2025]

Title:SYKI-SVC: Advancing Singing Voice Conversion with Post-Processing Innovations and an Open-Source Professional Testset

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Abstract:Singing voice conversion aims to transform a source singing voice into that of a target singer while preserving the original lyrics, melody, and various vocal techniques. In this paper, we propose a high-fidelity singing voice conversion system. Our system builds upon the SVCC T02 framework and consists of three key components: a feature extractor, a voice converter, and a post-processor. The feature extractor utilizes the ContentVec and Whisper models to derive F0 contours and extract speaker-independent linguistic features from the input singing voice. The voice converter then integrates the extracted timbre, F0, and linguistic content to synthesize the target speaker's waveform. The post-processor augments high-frequency information directly from the source through simple and effective signal processing to enhance audio quality. Due to the lack of a standardized professional dataset for evaluating expressive singing conversion systems, we have created and made publicly available a specialized test set. Comparative evaluations demonstrate that our system achieves a remarkably high level of naturalness, and further analysis confirms the efficacy of our proposed system design.
Comments:Accepted by ICASSP 2025
Subjects:Sound (cs.SD); Audio and Speech Processing (eess.AS)
Cite as:arXiv:2501.02953 [cs.SD]
 (orarXiv:2501.02953v1 [cs.SD] for this version)
 https://doi.org/10.48550/arXiv.2501.02953
arXiv-issued DOI via DataCite

Submission history

From: Yiquan Zhou [view email]
[v1] Mon, 6 Jan 2025 11:54:33 UTC (789 KB)
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