A multimodal machine learning framework fusing smartwatch audio and inertial sensing achieves macro F1 scores of 82% in lab and 77% in semi-naturalistic studies for detecting face-to-face conversations.
In Proceedings of the 8th International Conference on Mobile Systems, Applications, and Services (San Francisco, California, USA) (MobiSys ’10)
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.LG 1years
2025 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
Detecting In-Person Conversations in Noisy Real-World Environments with Smartwatch Audio and Motion Sensing
A multimodal machine learning framework fusing smartwatch audio and inertial sensing achieves macro F1 scores of 82% in lab and 77% in semi-naturalistic studies for detecting face-to-face conversations.