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arXiv · 2406.17801

A multi-speaker multi-lingual voice cloning system based on vits2 for limmits 2024 challenge

Xiaopeng Wang·Yi Lu·Xin Qi·Zhiyong Wang·Yuankun Xie·Shuchen Shi·Ruibo Fu
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Abstract

This paper presents the development of a speech synthesis system for the LIMMITS'24 Challenge, focusing primarily on Track 2. The objective of the challenge is to establish a multi-speaker, multi-lingual Indic Text-to-Speech system with voice cloning capabilities, covering seven Indian languages with both male and female speakers. The system was trained using challenge data and fine-tuned for few-shot voice cloning on target speakers. Evaluation included both mono-lingual and cross-lingual synthesis across all seven languages, with subjective tests assessing naturalness and speaker similarity. Our system uses the VITS2 architecture, augmented with a multi-lingual ID and a BERT model to enhance contextual language comprehension. In Track 1, where no additional data usage was permitted, our model achieved a Speaker Similarity score of 4.02. In Track 2, which allowed the use of extra data, it attained a Speaker Similarity score of 4.17.

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Xiaopeng Wang, Yi Lu, Xin Qi, Zhiyong Wang, Yuankun Xie, Shuchen Shi, Ruibo Fu. 2024-06-22. A multi-speaker multi-lingual voice cloning system based on vits2 for limmits 2024 challenge. https://arxiv.org/abs/2406.17801

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