FreeSVC: Towards Zero-shot Multilingual Singing Voice Conversion
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arXiv
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| Auteurs principaux: | , , , , , , , , |
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| Format: | Preprint |
| Publié: |
2025
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| _version_ | 1866916654282178560 |
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| author | Ferreira, Alef Iury Siqueira Gris, Lucas Rafael da Rosa, Augusto Seben de Oliveira, Frederico Santos Casanova, Edresson Sousa, Rafael Teixeira Junior, Arnaldo Candido Soares, Anderson da Silva Filho, Arlindo Galvão |
| author_facet | Ferreira, Alef Iury Siqueira Gris, Lucas Rafael da Rosa, Augusto Seben de Oliveira, Frederico Santos Casanova, Edresson Sousa, Rafael Teixeira Junior, Arnaldo Candido Soares, Anderson da Silva Filho, Arlindo Galvão |
| contents | This work presents FreeSVC, a promising multilingual singing voice conversion approach that leverages an enhanced VITS model with Speaker-invariant Clustering (SPIN) for better content representation and the State-of-the-Art (SOTA) speaker encoder ECAPA2. FreeSVC incorporates trainable language embeddings to handle multiple languages and employs an advanced speaker encoder to disentangle speaker characteristics from linguistic content. Designed for zero-shot learning, FreeSVC enables cross-lingual singing voice conversion without extensive language-specific training. We demonstrate that a multilingual content extractor is crucial for optimal cross-language conversion. Our source code and models are publicly available. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2501_05586 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | FreeSVC: Towards Zero-shot Multilingual Singing Voice Conversion Ferreira, Alef Iury Siqueira Gris, Lucas Rafael da Rosa, Augusto Seben de Oliveira, Frederico Santos Casanova, Edresson Sousa, Rafael Teixeira Junior, Arnaldo Candido Soares, Anderson da Silva Filho, Arlindo Galvão Sound Audio and Speech Processing This work presents FreeSVC, a promising multilingual singing voice conversion approach that leverages an enhanced VITS model with Speaker-invariant Clustering (SPIN) for better content representation and the State-of-the-Art (SOTA) speaker encoder ECAPA2. FreeSVC incorporates trainable language embeddings to handle multiple languages and employs an advanced speaker encoder to disentangle speaker characteristics from linguistic content. Designed for zero-shot learning, FreeSVC enables cross-lingual singing voice conversion without extensive language-specific training. We demonstrate that a multilingual content extractor is crucial for optimal cross-language conversion. Our source code and models are publicly available. |
| title | FreeSVC: Towards Zero-shot Multilingual Singing Voice Conversion |
| topic | Sound Audio and Speech Processing |
| url | https://arxiv.org/abs/2501.05586 |