Telesonar: Robocall Alarm System by Detecting Echo Channel and Breath Timing

Zhenyu Yan, Rui Tan, Qun Song, Chris Xiaoxuan Lu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Massive fraudulent and phishing robocalls present threats to societies. The integration of artificial intelligence technologies, including dialogue and voice generation systems, renders the robocalls more deceptive. Existing countermeasures such as caller ID, call provenance, voiceprint, and fake voice detection have respective limitations and are heavyweight for end users’ smartphones. This paper studies detecting the acoustic echo channel on the remote end of a call based on the received voice. The positive detection result evidencing the physical setup of an audio system is indicative of a human caller. However, the acoustic echo cancellation mechanisms of most audio systems and the use of earphone/headset diminish echoes significantly. To address these issues, the proposed Telesonar transmits short chirps during the vulnerable time of echo cancellation, detects the tiny echo remnants from the received voice, and passively analyzes the timing of caller’s breath sounds to confirm a human caller. Extensive real experiments under a wide range of settings show that Telesonar correctly recognizes human callers with a rate of over 95%, while wrongly recognizing voice robots as human with a rate of 3.8%.
Original languageEnglish
Title of host publicationProceedings of the 20th ACM Conference on Embedded Networked Sensor Systems (SenSys
Number of pages14
Publication statusAccepted/In press - 13 Oct 2022
EventThe 20th ACM Conference on Embedded Networked Sensor Systems, 2022 - Boston, United States
Duration: 6 Nov 20229 Nov 2022
Conference number: 20
http://sensys.acm.org/2022/

Conference

ConferenceThe 20th ACM Conference on Embedded Networked Sensor Systems, 2022
Abbreviated titleSenSys 2022
Country/TerritoryUnited States
CityBoston
Period6/11/229/11/22
Internet address

Keywords

  • mobile systems
  • robocall detection
  • internet-of-things systems

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