KIT's Submission to Cross-Lingual Voice Cloning in IWSLT 2026
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Computer Science > Computation and Language
Title:KIT's Submission to Cross-Lingual Voice Cloning in IWSLT 2026
Abstract:Cross-lingual voice cloning aims to generate speech in a target language while preserving speaker identity from a source-language reference. This task is central to speech translation and is the focus of the IWSLT 2026 Cross-Lingual Voice Cloning track. A key challenge is maintaining intelligibility and naturalness in the presence of accent variation and domain-specific vocabulary. We build on a multilingual text-to-speech model, FishAudio-S2-Pro, and introduce language tag prompting to improve language control and reduce accent leakage. We further apply reinforcement learning (RL) fine-tuning for task adaptation and observe improvements in intelligibility. Finally, we propose a reference-conditioned lexical matching method that improves pronunciation of domain-specific terms when lexical overlap is present. Results show that language prompting provides the largest gains, while lexical matching yields consistent improvements on matched subsets.
| Subjects: | Computation and Language (cs.CL); Sound (cs.SD) |
| Cite as: | arXiv:2606.07240 [cs.CL] |
| (or arXiv:2606.07240v1 [cs.CL] for this version) | |
| https://doi.org/10.48550/arXiv.2606.07240
arXiv-issued DOI via DataCite (pending registration)
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