Transferring Source Style in Non-Parallel Voice Conversion
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Abstract (arXiv)
Voice conversion (VC) techniques aim to modify speaker identity of an utterance while preserving the underlying linguistic information. Most VC approaches ignore modeling of the speaking style (e.g. emotion and emphasis), which may contain the factors intentionally added by the speaker and should be retained during conversion. This study proposes a sequence-to-sequence based non-parallel VC approach, which has the capability of transferring the speaking style from the source speech to the converted speech by explicitly modeling. Objective evaluation and subjective listening tests show superiority of the proposed VC approach in terms of speech naturalness and speaker similarity of the converted speech. Experiments are also conducted to show the source-style transferability of the proposed approach.
Key facts. Cited by 7 papers in the map (data through 7 Oct 2026). First posted on arXiv 19 May 2020.
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Citing papers per year: 2021: 3; 2022: 3; 2023: 0; 2024: 0; 2025: 1.
7 papers.
- 2021Emotional Voice Conversion: Theory, Databases and ESDcited by 113
- 2022An Overview of Affective Speech Synthesis and Conversion in the Deep Learning Eracited by 32
- 2021Assem-VC: Realistic Voice Conversion by Assembling Modern Speech Synthesis Techniquescited by 11
- 2022A Comparative Study of Self-supervised Speech Representation Based Voice Conversioncited by 9
- 2025Prosody-Adaptable Audio Codecs for Zero-Shot Voice Conversion via In-Context Learningcited by 6
- 2021On Prosody Modeling for ASR+TTS based Voice Conversioncited by 3
- 2022DisC-VC: Disentangled and F0-Controllable Neural Voice Conversioncited by 0
- 2025Prosody-Adaptable Audio Codecs for Zero-Shot Voice Conversion via In-Context Learning21 May 2025
- 2022DisC-VC: Disentangled and F0-Controllable Neural Voice Conversion20 Oct 2022
- 2022An Overview of Affective Speech Synthesis and Conversion in the Deep Learning Era6 Oct 2022
- 2022A Comparative Study of Self-supervised Speech Representation Based Voice Conversion10 Jul 2022
- 2021On Prosody Modeling for ASR+TTS based Voice Conversion20 Jul 2021
- 2021Emotional Voice Conversion: Theory, Databases and ESD31 May 2021
- 2021Assem-VC: Realistic Voice Conversion by Assembling Modern Speech Synthesis Techniques2 Apr 2021