  This paper presents the results and analyses stemming from the first
VoicePrivacy 2020 Challenge which focuses on developing anonymization solutions
for speech technology. We provide a systematic overview of the challenge design
with an analysis of submitted systems and evaluation results. In particular, we
describe the voice anonymization task and datasets used for system development
and evaluation. Also, we present different attack models and the associated
objective and subjective evaluation metrics. We introduce two anonymization
baselines and provide a summary description of the anonymization systems
developed by the challenge participants. We report objective and subjective
evaluation results for baseline and submitted systems. In addition, we present
experimental results for alternative privacy metrics and attack models
developed as a part of the post-evaluation analysis. Finally, we summarize our
insights and observations that will influence the design of the next
VoicePrivacy challenge edition and some directions for future voice
anonymization research.
