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This paper presents the details of Task 1A Acoustic Scene Classification inthe DCASE 2021 Challenge. The task targeted development of low-complexitysolutions with good generalization properties. The provided baseline system isbased on a CNN architecture and post-training quantization of parameters. Thesystem is trained using all the available training data, without any specifictechnique for handling device mismatch, and obtains an overall accuracy of47.7%, with a log loss of 1.473. The task received 99 submissions from 30teams, and most of the submitted systems outperformed the baseline. The mostused techniques among the submissions were residual networks and weightquantization, with the top systems reaching over 70% accuracy, and log lossunder 0.8. The acoustic scene classification task remained a popular task inthe challenge, despite the increasing difficulty of the setup.

Low-complexity acoustic scene classification for multi-device audio: analysis of DCASE 2021 Challenge systems