A unified one-shot prosody and speaker conversion system with self-supervised discrete speech units
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Abstract (arXiv)
We present a unified system to realize one-shot voice conversion (VC) on the pitch, rhythm, and speaker attributes. Existing works generally ignore the correlation between prosody and language content, leading to the degradation of naturalness in converted speech. Additionally, the lack of proper language features prevents these systems from accurately preserving language content after conversion. To address these issues, we devise a cascaded modular system leveraging self-supervised discrete speech units as language representation. These discrete units provide duration information essential for rhythm modeling. Our system first extracts utterance-level prosody and speaker representations from the raw waveform. Given the prosody representation, a prosody predictor estimates pitch, energy, and duration for each discrete unit in the utterance. A synthesizer further reconstructs speech based on the predicted prosody, speaker representation, and discrete units. Experiments show that our system outperforms previous approaches in naturalness, intelligibility, speaker transferability, and prosody transferability. Code and samples are publicly available.
Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). Builds on 24 of its 30 references that are in the map. First posted on arXiv 12 Nov 2022.
Builds on
24 of 30 references.
References · 24
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12 more
- 2021Neural Analysis and Synthesis: Reconstructing Speech from Self-Supervised Representationscited by 81
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Citing papers per year: 2022: 1; 2023: 0; 2024: 1; 2025: 1.
3 papers.
- 2022Speaking Style Conversion in the Waveform Domain Using Discrete Self-Supervised Unitscited by 15
- 2024vec2wav 2.0: Advancing Voice Conversion via Discrete Token Vocoderscited by 6
- 2025Towards Inclusive ASR: Investigating Voice Conversion for Dysarthric Speech Recognition in Low-Resource Languagescited by 3
- 2025Towards Inclusive ASR: Investigating Voice Conversion for Dysarthric Speech Recognition in Low-Resource Languages20 May 2025
- 2024vec2wav 2.0: Advancing Voice Conversion via Discrete Token Vocoders3 Sep 2024
- 2022Speaking Style Conversion in the Waveform Domain Using Discrete Self-Supervised Units19 Dec 2022