The Voice Conversion Challenge 2018: Promoting Development of Parallel and Nonparallel Methods
This work addresses the need for standardized benchmarks in voice conversion research, but it is incremental as it builds on a previous challenge.
The Voice Conversion Challenge 2018 provided a common framework for evaluating voice conversion systems, with 23 teams submitting systems and a crowdsourced evaluation showing results for naturalness and similarity.
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.