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arXiv · 2411.00064

The ISCSLP 2024 Conversational Voice Clone (CoVoC) Challenge: Tasks, Results and Findings

Kangxiang Xia·Dake Guo·Jixun Yao·Liumeng Xue·Hanzhao Li·Shuai Wang·Zhao Guo·Lei Xie·Qingqing Zhang·Lei Luo·Minghui Dong·Peng Sun
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Abstract

The ISCSLP 2024 Conversational Voice Clone (CoVoC) Challenge aims to benchmark and advance zero-shot spontaneous style voice cloning, particularly focusing on generating spontaneous behaviors in conversational speech. The challenge comprises two tracks: an unconstrained track without limitation on data and model usage, and a constrained track only allowing the use of constrained open-source datasets. A 100-hour high-quality conversational speech dataset is also made available with the challenge. This paper details the data, tracks, submitted systems, evaluation results, and findings.

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Kangxiang Xia, Dake Guo, Jixun Yao, Liumeng Xue, Hanzhao Li, Shuai Wang, Zhao Guo, Lei Xie, Qingqing Zhang, Lei Luo, Minghui Dong, Peng Sun. 2024-10-31. The ISCSLP 2024 Conversational Voice Clone (CoVoC) Challenge: Tasks, Results and Findings. https://arxiv.org/abs/2411.00064

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