  The DCASE 2018 Challenge consists of five tasks related to automatic
classification and detection of sound events and scenes. This paper presents
the setup of Task 5 which includes the description of the task, dataset and the
baseline system. In this task, it is investigated to which extent multi-channel
acoustic recordings are beneficial for the purpose of classifying domestic
activities. The goal is to exploit spectral and spatial cues independent of
sensor location using multi-channel audio. For this purpose we provided a
development and evaluation dataset which are derivatives of the SINS database
and contain domestic activities recorded by multiple microphone arrays. The
baseline system, based on a Neural Network architecture using convolutional and
dense layer(s), is intended to lower the hurdle to participate the challenge
and to provide a reference performance.
