ISCA Archive Interspeech 2021
ISCA Archive Interspeech 2021

An Evaluation of Data Augmentation Methods for Sound Scene Geotagging

Helen L. Bear, Veronica Morfi, Emmanouil Benetos

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.


doi: 10.21437/Interspeech.2021-1837

Cite as: Bear, H.L., Morfi, V., Benetos, E. (2021) An Evaluation of Data Augmentation Methods for Sound Scene Geotagging. Proc. Interspeech 2021, 581-585, doi: 10.21437/Interspeech.2021-1837

@inproceedings{bear21_interspeech,
  author={Helen L. Bear and Veronica Morfi and Emmanouil Benetos},
  title={{An Evaluation of Data Augmentation Methods for Sound Scene Geotagging}},
  year=2021,
  booktitle={Proc. Interspeech 2021},
  pages={581--585},
  doi={10.21437/Interspeech.2021-1837}
}