Audio Analysis as a Control Knob for Social Sensing

Abstract While humans can act as e‚ffective sensors, human input is subject to a high degree of error and highly dependent on the context. Furthermore, extracting the signal from the noise for social sensing is a dicult challenge. One approach to improving the accuracy of social sensing is to use physical sensors as a control knob for social sensing algorithms. In this paper, we present an architecture for using audio sensors as a way to control an algorithm used for social sensing of interesting events. We present various use cases where the architecture is applicable, and go into the details of one speci€fic use case, namely using crowd behavior in a golf-course to identify and control social media feeds related to the course.
  • Dinesh Verma (IBM US)
  • Bongjun Ko (IBM US)
  • Shiqiang Wang (IBM US)
  • Xiping Wang (IBM US)
  • Graham Bent (IBM UK)
Date Apr-2017
Venue International Workshop on Social Sensing 2017