  Sound scene geotagging is a new topic of research which has evolved from
acoustic scene classification. It is motivated by the idea of audio
surveillance. Not content with only describing a scene in a recording, a
machine which can locate where the recording was captured would be of use to
many. In this paper we explore a series of common audio data augmentation
methods to evaluate which best improves the accuracy of audio geotagging
classifiers. Our work improves on the state-of-the-art city geotagging method
by 23% in terms of classification accuracy.
