  City-identification of videos aims to determine the likelihood of a video
belonging to a set of cities. In this paper, we present an approach using only
audio, thus we do not use any additional modality such as images, user-tags or
geo-tags. In this manner, we show to what extent the city-location of videos
correlates to their acoustic information. Success in this task suggests
improvements can be made to complement the other modalities. In particular, we
present a method to compute and use semantic acoustic features to perform
city-identification and the features show semantic evidence of the
identification. The semantic evidence is given by a taxonomy of urban sounds
and expresses the potential presence of these sounds in the city- soundtracks.
We used the MediaEval Placing Task set, which contains Flickr videos labeled by
city. In addition, we used the UrbanSound8K set containing audio clips labeled
by sound- type. Our method improved the state-of-the-art performance and
provides a novel semantic approach to this task
