arXiv cs.CL· Yuanzhong Zheng, Wei Huang, Ming Ma, Kailun Jin, Youhai Jiang·· 13 小时前AI 评分31
闭环双参考引导:跨语言语音克隆中的口音控制
Closed-Loop Dual-Reference Guidance for Accent Control in Cross-Lingual Voice Cloning
AI 导读
研究提出闭环双参考引导方法,将原始参考语音与经语音转换构建的可复用母语锚点配对,分别初始化独立的语言模型状态以引导共享声学轨迹。在20名留出法语说话人上,固定设置 λ*=0.33 使残留法语 LID 质量较直接克隆降低 73%,ECAPA 相似度仅损失 0.042,平均 WER 为 0.009、平均 GOP 为 4.750,均为测试组最优。
正文 · 原文
Abstract:Zero-shot cross-lingual voice cloning often carries the reference speaker's accent into the target language. We propose closed-loop dual-reference guidance, which pairs the original reference with a reusable native anchor constructed by voice conversion (VC). The references initialize separate language-model (LM) states that guide a shared acoustic trajectory; each completed patch then updates both states, keeping their generated histories aligned with the emitted speech. Anchor construction runs once per speaker, and online synthesis uses a frozen TTS model without per-utterance VC. On 20 held-out French speakers, the fixed setting $\lambda^{\!*}=0.33$ reduces residual French LID mass by 73\% versus direct cloning, at an ECAPA similarity cost of only $0.042$; relative to anchor-only cloning, it recovers $0.155$. The method achieves the lowest mean WER ($0.009$) and highest mean GOP ($4.750$) among the held-out test arms. In blinded preference tests, native-English listeners favor it over direct cloning on pronunciation naturalness, and over both anchor-only cloning and a TTS$\to$VC cascade on speaker identity. Online RTF is approximately 26\% lower than the cascade's ($0.59$ vs.\ $0.80$), and the same setting reduces Spanish LID mass by 56\% without re-tuning.
| Subjects: | Sound (cs.SD); Computation and Language (cs.CL); Machine Learning (cs.LG); Audio and Speech Processing (eess.AS) |
| Cite as: | arXiv:2610.29351 [cs.SD] |
| (or arXiv:2610.29351v1 [cs.SD] for this version) | |
| https://doi.org/10.48550/arXiv.2610.29351 arXiv-issued DOI via DataCite (pending registration) |
Submission history
From: Yuanzhong Zheng [view email]
[v1]
Wed, 21 Oct 2026 07:46:22 UTC (1,417 KB)
来源:arXiv cs.CL · arxiv.org