  This paper describes a pipeline for collecting acoustic scene data by using
crowdsourcing. The detailed process of crowdsourcing is explained, including
planning, validation criteria, and actual user interfaces. As a result of data
collection, we present CochlScene, a novel dataset for acoustic scene
classification. Our dataset consists of 76k samples collected from 831
participants in 13 acoustic scenes. We also propose a manual data split of
training, validation, and test sets to increase the reliability of the
evaluation results. Finally, we provide a baseline system for future research.
