The ISCSLP 2024 Conversational Voice Clone (CoVoC) Challenge: Tasks, Results and Findings
- URL: http://arxiv.org/abs/2411.00064v1
- Date: Thu, 31 Oct 2024 09:39:49 GMT
- Title: The ISCSLP 2024 Conversational Voice Clone (CoVoC) Challenge: Tasks, Results and Findings
- Authors: Kangxiang Xia, Dake Guo, Jixun Yao, Liumeng Xue, Hanzhao Li, Shuai Wang, Zhao Guo, Lei Xie, Qingqing Zhang, Lei Luo, Minghui Dong, Peng Sun,
- Abstract summary: The ISCSLP 2024 Conversational Voice Clone (CoVoC) Challenge aims to benchmark and advance zero-shot spontaneous style voice cloning.
This paper details the data, tracks, submitted systems, evaluation results, and findings.
- Score: 18.994388357437924
- License:
- 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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