k-SpecNET: Localization and classification of indoor superimposed sound for acoustic sensor networks

Wei Wang, Fatjon Seraj, Paul J.M. Havinga

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Abstract

Automatic localization and classification of environmental sound events can provide great aid to many human-centric applications. However as many papers have mentioned, environmental sound events in daily life are complicated and hard to classify especially when multiple sounds happen simultaneously. Being different from many other works, we use an acoustic-sensor-network to solve this problem and decompose overlapping sound events using a sound localization model. The core of our contribution is to first find and locate the keypoints from each microphone's spectrogram and then aggregate them. With these aggregated keypoints as input, we then use 2 different classification models to further classify the type of sound sources. Compared with other classification models that only use single microphone, our experiments show that our solution is both accurate and low-cost in terms of calculation effort.
Original languageEnglish
Title of host publication2020 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops)
Place of PublicationPiscataway, NJ
PublisherIEEE
Number of pages6
ISBN (Electronic)978-1-7281-4716-1
ISBN (Print)978-1-7281-4717-8
DOIs
Publication statusPublished - 4 Aug 2020
Event2020 IEEE International Conference on Pervasive Computing and Communications Workshops, PerCom 2020 - University of Austin, Austin, United States
Duration: 23 Mar 202027 Mar 2020
Conference number: 18
http://percom.org/Previous/ST2020/

Conference

Conference2020 IEEE International Conference on Pervasive Computing and Communications Workshops, PerCom 2020
Abbreviated titlePerCom
Country/TerritoryUnited States
CityAustin
Period23/03/2027/03/20
Internet address

Keywords

  • Convolutional Neural Networks
  • Deep Neural Network
  • Environmental sound localization
  • Keypoints localization
  • TDOA
  • acoustic sensors
  • superimposed sound
  • 22/2 OA procedure

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