  Automatic speech recognition (ASR) has been significantly advanced with the
use of deep learning and big data. However improving robustness, including
achieving equally good performance on diverse speakers and accents, is still a
challenging problem. In particular, the performance of children speech
recognition (CSR) still lags behind due to 1) the speech and language
characteristics of children's voice are substantially different from those of
adults and 2) sizable open dataset for children speech is still not available
in the research community. To address these problems, we launch the Children
Speech Recognition Challenge (CSRC), as a flagship satellite event of IEEE SLT
2021 workshop. The challenge will release about 400 hours of Mandarin speech
data for registered teams and set up two challenge tracks and provide a common
testbed to benchmark the CSR performance. In this paper, we introduce the
datasets, rules, evaluation method as well as baselines.
