Sounds Aware

            
@inproceedings{2019_13,
  abstract = {Sounds Aware is a web application that runs on a smartphone and uses machine learning to detect human-made sound (anthrophony) and masks it with ambient music as a user walks around their environment. A study was completed to determine if this app is an effective means of shifting a user's attention away from anthrophony and to biological (biophony) and geophysical (geophony) sounds while walking and encouraging environmental awareness. Though the model is pre-trained with the author's local environmental sounds, the user can train the model further on their unique soundscape so that each user gets a personalized experience. After the training process, the user can listen to ambient music based on traits of the surrounding anthrophony. If the app senses less anthrophony and more biophony or geophony, then the music fades away, bringing the user's attention to the anthrophony.},
  address = {Trondheim, Norway},
  author = {Carson, Tate},
  booktitle = {Proceedings of the International Web Audio Conference},
  editor = {Xambó, Anna and Martín, Sara R. and Roma, Gerard},
  month = {December},
  pages = {139--140},
  publisher = {NTNU},
  series = {WAC '19},
  title = {Sounds Aware},
  year = {2019},
  ISSN = {2663-5844}
}