English

The Voice Conversion Challenge 2018: Promoting Development of Parallel and Nonparallel Methods

Audio and Speech Processing 2018-04-13 v1 Computation and Language Sound Machine Learning

Abstract

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.

Keywords

Cite

@article{arxiv.1804.04262,
  title  = {The Voice Conversion Challenge 2018: Promoting Development of Parallel and Nonparallel Methods},
  author = {Jaime Lorenzo-Trueba and Junichi Yamagishi and Tomoki Toda and Daisuke Saito and Fernando Villavicencio and Tomi Kinnunen and Zhenhua Ling},
  journal= {arXiv preprint arXiv:1804.04262},
  year   = {2018}
}

Comments

Accepted for Speaker Odyssey 2018

R2 v1 2026-06-23T01:21:07.806Z