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Speech Content Factorization

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Universal Speech Content Factorization

arXiv:2603.08977v2 Announce Type: replace-cross Abstract: We propose Universal Speech Content Factorization (USCF), a simple and invertible linear method for extracting a low-rank speech representation in which speaker timbre is suppressed while phonetic content is preserved. USCF extends Speech Content Factorization, a closed-set voice conversion (VC) method, to an open-set setting by learning a universal speech-to-content mapping via least-squares optimization and deriving speaker-specific...

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UniVoice: A Unified Model for Speech and Singing Voice Generation

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