  Audio deepfake detection is an emerging topic in the artificial intelligence
community. The second Audio Deepfake Detection Challenge (ADD 2023) aims to
spur researchers around the world to build new innovative technologies that can
further accelerate and foster research on detecting and analyzing deepfake
speech utterances. Different from previous challenges (e.g. ADD 2022), ADD 2023
focuses on surpassing the constraints of binary real/fake classification, and
actually localizing the manipulated intervals in a partially fake speech as
well as pinpointing the source responsible for generating any fake audio.
Furthermore, ADD 2023 includes more rounds of evaluation for the fake audio
game sub-challenge. The ADD 2023 challenge includes three subchallenges: audio
fake game (FG), manipulation region location (RL) and deepfake algorithm
recognition (AR). This paper describes the datasets, evaluation metrics, and
protocols. Some findings are also reported in audio deepfake detection tasks.
