We present the Voice Conversion Challenge 2018, designed as a follow up to the 2016 edition with the aim of providing a common framework for evaluating and comparing different state-of-the-art voice conversion (VC) systems. The objective of the challenge was to perform speaker conversion (i.e.\ transform the vocal identity) of a source speaker to a target speaker while maintaining linguistic information. As an update to the previous challenge, we considered both parallel and non-parallel data to form the Hub and Spoke tasks, respectively. A total of 23 teams from around the world submitted their systems, 11 of them additionally participated in the optional Spoke task. A large-scale crowdsourced perceptual evaluation was then carried out to rate the submitted converted speech in terms of naturalness and similarity to the target speaker identity. In this paper, we present a brief summary of the state-of-the-art techniques for VC, followed by a detailed explanation of the challenge tasks and the results that were obtained.
Cite as: Lorenzo-Trueba, J., Yamagishi, J., Toda, T., Saito, D., Villavicencio, F., Kinnunen, T., Ling, Z. (2018) The Voice Conversion Challenge 2018: Promoting Development of Parallel and Nonparallel Methods . Proc. The Speaker and Language Recognition Workshop (Odyssey 2018), 195-202, doi: 10.21437/Odyssey.2018-28
@inproceedings{lorenzotrueba18_odyssey,
author={Jaime Lorenzo-Trueba and Junichi Yamagishi and Tomoki Toda and Daisuke Saito and Fernando Villavicencio and Tomi Kinnunen and Zhenhua Ling},
title={{The Voice Conversion Challenge 2018: Promoting Development of Parallel and Nonparallel Methods }},
year=2018,
booktitle={Proc. The Speaker and Language Recognition Workshop (Odyssey 2018)},
pages={195--202},
doi={10.21437/Odyssey.2018-28}
}