Voice conversion (VC) is a technique to transform a speaker identity included in a source speech waveform into a different one while preserving linguistic information of the source speech waveform. In 2020, we launched the third edition of VCC, the VCC 2020 [1]. This repository contains all converted audios submitted by 33 participating teams. The training and evaluation dataset can be found at [2]. The crowdsourcing listening test related data and results can be found at [3]. The summary, subjective evluation analysis and objective assessment of this challenge can be found in [1] and [4]. [1] Yi Zhao, Wen-Chin Huang, Xiaohai Tian, Junichi Yamagishi, Rohan Kumar Das, Tomi Kinnunen, Zhenhua Ling, and Tomoki Toda. "Voice conversion challenge 2020: Intra-lingual semi-parallel and cross-lingual voice conversion" Proc. Joint Workshop for the Blizzard Challenge and Voice Conversion Challenge 2020, 80-98, DOI: 10.21437/VCC_BC.2020-14. [2] Yi Zhao, Wen-Chin Huang, Xiaohai Tian, Junichi Yamagishi,Rohan Kumar Das, Tomi Kinnunen, Zhenhua Ling, Tomoki Toda. Voice Conversion Challenge 2020 database v1.0, 2020, 10.5281/zenodo.4345689. [3]Yi Zhao, Wen-Chin Huang, Xiaohai Tian, Junichi Yamagishi, Rohan Kumar Das, Tomi Kinnunen, Zhenhua Ling, and Tomoki Toda. "Voice Conversion Challenge 2020 Listening Test Data." DOI: 10.5281/zenodo.4433173 [4]Das RK, Kinnunen T, Huang WC, Ling Z, Yamagishi J, Zhao Y, Tian X, Toda T. Predictions of subjective ratings and spoofing assessments of voice conversion challenge 2020 submissions. arXiv preprint arXiv:2009.03554. 2020 Sep 8. ————————————————————————————————————————————————— Data structure: team**/wavs/TargetSpeaker_SourceSpeaker.wav —————————————————————————————————————————————————