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arXiv · 2505.22054

Voice Adaptation for Swiss German

Samuel Stucki·Jan Deriu·Mark Cieliebak
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Abstract

This work investigates the performance of Voice Adaptation models for Swiss German dialects, i.e., translating Standard German text to Swiss German dialect speech. For this, we preprocess a large dataset of Swiss podcasts, which we automatically transcribe and annotate with dialect classes, yielding approximately 5000 hours of weakly labeled training material. We fine-tune the XTTSv2 model on this dataset and show that it achieves good scores in human and automated evaluations and can correctly render the desired dialect. Our work shows a step towards adapting Voice Cloning technology to underrepresented languages. The resulting model achieves CMOS scores of up to -0.28 and SMOS scores of 3.8.

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Samuel Stucki, Jan Deriu, Mark Cieliebak. 2025-05-28. Voice Adaptation for Swiss German. https://arxiv.org/abs/2505.22054

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