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New method enhances cross-lingual voice cloning with accent control · 3 sources tracked

By PulseAugur Editorial · [3 sources] ·

Researchers have developed a new method called Closed-Loop Dual-Reference Guidance to improve cross-lingual voice cloning by controlling accents. This technique pairs the original reference speaker with a reusable native anchor, which helps maintain the desired accent in the cloned voice. The system demonstrated a significant reduction in accent leakage and improved speaker identity compared to direct cloning methods, while also being more efficient for real-time synthesis. AI

IMPACT Advances in accent control for voice cloning and unlearning in recommendation systems.

RANK_REASON The cluster contains two distinct academic papers submitted to arXiv, one on voice cloning and another on recommendation systems, fitting the research category.

Read on arXiv cs.LG →

AI-generated summary · Google Gemini · from 3 sources. How we write summaries →

New method enhances cross-lingual voice cloning with accent control · 3 sources tracked

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The cluster contains two distinct academic papers submitted to arXiv, one on voice cloning and another on recommendation systems, fitting the research category.
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3 independent sources
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4 days old
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COVERAGE [3]

  1. arXiv cs.CL TIER_1 English(EN) · Yuanzhong Zheng, Wei Huang, Ming Ma, Kailun Jin, Youhai Jiang ·

    Closed-Loop Dual-Reference Guidance for Accent Control in Cross-Lingual Voice Cloning

    arXiv:2610.29351v1 Announce Type: cross 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 construc…

  2. arXiv cs.LG TIER_1 English(EN) · Pierre Lubitzsch, Yubao Tang, Maarten de Rijke, Sebastian Schelter ·

    Neighborhood-Aware Unlearning for Generative Recommendation

    arXiv:2610.27232v1 Announce Type: cross Abstract: Generative recommendation predicts items by autoregressively generating semantic identifiers (SIDs), whose tokens are shared across semantically related items. With this paradigm gaining adoption, the question of how to support un…

  3. arXiv cs.IR (Information Retrieval) TIER_1 English(EN) · Sebastian Schelter ·

    Neighborhood-Aware Unlearning for Generative Recommendation

    Generative recommendation predicts items by autoregressively generating semantic identifiers (SIDs), whose tokens are shared across semantically related items. With this paradigm gaining adoption, the question of how to support unlearning in it has become pressing. If training in…

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