Title
Cross-Modal Approach for Conversational Well-being Monitoring with Multi-Sensory Earables.
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.
Year
DOI
Venue
2018
10.1145/3267305.3267695
UbiComp '18: The 2018 ACM International Joint Conference on Pervasive and Ubiquitous Computing Singapore Singapore October, 2018
Keywords
Field
DocType
Earable, well-being, multi-sensory
Conversation,Computer science,Human–computer interaction,Well-being,Inertial measurement unit,Sensory system,Microphone,Modal
Conference
ISBN
Citations 
PageRank 
978-1-4503-5966-5
0
0.34
References 
Authors
3
5
Name
Order
Citations
PageRank
Chulhong Min136230.13
Alessandro Montanari275.02
Akhil Mathur310115.10
Seungchul Lee4327.10
Fahim Kawsar590980.24