Acoustic Scene Classification in DCASE 2019 Challenge: Closed and Open Set Classification and Data Mismatch Setups

Abstract

Acoustic Scene Classification is a regular task in the DCASE Challenge, with each edition having it as a task. Throughout the years, modifications to the task have included mostly changing the dataset and increasing its size, but recently also more realistic setups have been introduced. In DCASE 2019 Challenge, the Acoustic Scene Classification task includes three subtasks: Subtask A, a closed-set typical supervised classification where all data is recorded with the same device; Subtask B, a closed-set classification setup with mismatched recording devices between training and evaluation data, and Subtask C, an open-set classification setup in which evaluation data could contain acoustic scenes not encountered in the training. In all subtasks, the provided baseline system was significantly outperformed, with top performance being 85.2% for Subtask A, 75.5% for Subtask B, and 67.4% for Subtask C. This paper presents the outcome of DCASE 2019 Challenge Task 1 in terms of submitted systems performance and analysis.