Cross-modal approach for conversational well-being monitoring with multi-sensory earables

Chulhong Min, Alessandro Montanari, Akhil Mathur, Seungchul Lee, Fahim Kawsar

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

2 Citations (Scopus)

Abstract

We propose a cross-modal approach for conversational well-being monitoring with a multi-sensory earable. It consists of motion, audio, and BLE models on earables. Using the IMU sensor, the microphone, and BLE scanning, the models detect speaking activities, stress and emotion, and participants in the conversation, respectively. We discuss the feasibility in qualifying conversations with our purpose-built cross-modal model in an energy-efficient and privacy-preserving way. With the cross-modal model, we develop a mobile application that qualifies on-going conversations and provides personalised feedback on social well-being.

Original languageEnglish
Title of host publicationUbiComp/ISWC 2018 - Adjunct Proceedings of the 2018 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2018 ACM International Symposium on Wearable Computers
EditorsRajesh K. Balan, Youngki Lee, Kai Kunze
Place of PublicationNew York, NY, USA
PublisherAssociation for Computing Machinery (ACM)
Pages706-709
Number of pages4
ISBN (Electronic)978-1-4503-5966-5
DOIs
Publication statusPublished - 2018
Event2018 Joint ACM International Conference on Pervasive and Ubiquitous Computing, UbiComp 2018 and 2018 ACM International Symposium on Wearable Computers, ISWC 2018 - Singapore, Singapore
Duration: 8 Oct 201812 Oct 2018

Conference

Conference2018 Joint ACM International Conference on Pervasive and Ubiquitous Computing, UbiComp 2018 and 2018 ACM International Symposium on Wearable Computers, ISWC 2018
CountrySingapore
CitySingapore
Period8/10/1812/10/18

Keywords

  • Earable
  • Multi-sensory
  • Well-being

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