  This paper introduces the fifth oriental language recognition (OLR) challenge
AP20-OLR, which intends to improve the performance of language recognition
systems, along with APSIPA Annual Summit and Conference (APSIPA ASC). The data
profile, three tasks, the corresponding baselines, and the evaluation
principles are introduced in this paper. The AP20-OLR challenge includes more
languages, dialects and real-life data provided by Speechocean and the NSFC
M2ASR project, and all the data is free for participants. The challenge this
year still focuses on practical and challenging problems, with three tasks: (1)
cross-channel LID, (2) dialect identification and (3) noisy LID. Based on Kaldi
and Pytorch, recipes for i-vector and x-vector systems are also conducted as
baselines for the three tasks. These recipes will be online-published, and
available for participants to configure LID systems. The baseline results on
the three tasks demonstrate that those tasks in this challenge are worth paying
more efforts to achieve better performance.
