  This paper presents the details of Task 1A Acoustic Scene Classification in
the DCASE 2021 Challenge. The task targeted development of low-complexity
solutions with good generalization properties. The provided baseline system is
based on a CNN architecture and post-training quantization of parameters. The
system is trained using all the available training data, without any specific
technique for handling device mismatch, and obtains an overall accuracy of
47.7%, with a log loss of 1.473. The task received 99 submissions from 30
teams, and most of the submitted systems outperformed the baseline. The most
used techniques among the submissions were residual networks and weight
quantization, with the top systems reaching over 70% accuracy, and log loss
under 0.8. The acoustic scene classification task remained a popular task in
the challenge, despite the increasing difficulty of the setup.
