A paper about the DCASE2017 Challenge tasks will be published in the upcoming DCASE2017 Workshop. Please cite this paper when referring to the DCASE2017 Challenge in your publications about DCASE2017:
A. Mesaros, T. Heittola, A. Diment, B. Elizalde, A. Shah, E. Vincent, B. Raj, and T. Virtanen. DCASE 2017 challenge setup: tasks, datasets and baseline system. In Proceedings of the Detection and Classification of Acoustic Scenes and Events 2017 Workshop (DCASE2017), 85–92. November 2017.
DCASE 2017 Challenge Setup: Tasks, Datasets and Baseline System
Abstract
DCASE 2017 Challenge consists of four tasks: acoustic scene classification, detection of rare sound events, sound event detection in real-life audio, and large-scale weakly supervised sound event detection for smart cars. This paper presents the setup of these tasks: task definition, dataset, experimental setup, and baseline system results on the development dataset. The baseline systems for all tasks rely on the same implementation using multilayer perceptron and log mel-energies, but differ in the structure of the output layer and the decision making process, as well as the evaluation of system output using task specific metrics.
Keywords
Sound scene analysis, Acoustic scene classification, Sound event detection, Audio tagging, Rare sound events