The sound of silence

Wai Tian Tan, Mary Baker, Bowon Lee, Ramin Samadani

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

23 Scopus citations

Abstract

A list of the dynamically changing group membership of a meeting supports a variety of meeting-related activities. Effortless content sharing might be the most important ap- plication, but we can also use it to provide business card information for attendees, feed information into calendar ap-plications to simplify scheduling of follow-up meetings, pop-ulate the membership of collaborative editing applications, mailing lists, and social networks, and perform many other tasks. We have developed a system that uses audio sensing to maintain meeting membership automatically. We choose au- dio since hearing the same conversation provides a human-centric notion of attending the same gathering. It takes into account walls and other sound barriers between otherwise closely situated people. It can sense participants attending remotely by teleconference. It does not require attendees to perform any explicit action when participants leave a meet-ing for which they should no longer have access to associ-ated content. It works indoors and outdoors and does not require pre-populating databases with mapping information. For sensors, we require only the commonly available micro- phones on mobile devices. Our system exploits a new technique for matching sensed patterns of relative audio silence, or silence signatures, from mobile devices (mobile phones, tablets, laptops) to deter-mine device co-location. A signature based on simple si-lence patterns rather than a detailed audio characterization reveals less information about the content of potentially private conversations and is also more robustly compared across devices that are not clock synchronized. We evaluate our method in formal indoor meetings and teleconferences and in ad hoc gatherings outdoors and in a noisy cafeteria. Across all our tests so far, our approach determines audio co-location with a worst-case accuracy of 96%, and recovery from these errors takes only a few seconds. We also describe a content sharing application supported by silence signature.

Original languageEnglish
Title of host publicationSenSys 2013 - Proceedings of the 11th ACM Conference on Embedded Networked Sensor Systems
PublisherAssociation for Computing Machinery
ISBN (Print)9781450320276
DOIs
StatePublished - 2013
Externally publishedYes
Event11th ACM Conference on Embedded Networked Sensor Systems, SenSys 2013 - Rome, Italy
Duration: 11 Nov 201315 Nov 2013

Publication series

NameSenSys 2013 - Proceedings of the 11th ACM Conference on Embedded Networked Sensor Systems

Conference

Conference11th ACM Conference on Embedded Networked Sensor Systems, SenSys 2013
Country/TerritoryItaly
CityRome
Period11/11/1315/11/13

Keywords

  • Audio
  • Content sharing
  • Localization
  • Mobile cloud services
  • Mobile sensing
  • Mobile systems
  • Silence signatures

Fingerprint

Dive into the research topics of 'The sound of silence'. Together they form a unique fingerprint.

Cite this