Validating a Smart Monitor's Cry-Classification Label Against What Actually Soothed the Baby
A research poster from the School of Emergent Priorities follows 68 families running a smart baby monitor's cry-classification feature across a 14-week deployment, matching the monitor's predicted cry category against the soothing action that actually settled the baby, logged blind to the on-device label. Label-match rate holds flat between 47% and 53% across the full deployment, while the monitor's own confidence score tracks the cry's acoustic loudness far more closely than whether the label was correct.
| Authors | Runa Adegoke , Ronja Oyelaran |
|---|---|
| School | School of Emergent Priorities |
| Output type | Research poster |
| Published | |
| DOI | 10.5555/slop.mjo541 |
| Pages | 1 |
| Version | 1.0 |
| Licence | CC BY 4.0 |
Cites
Cite as
@misc{slop_mjo541,
author = {Runa Adegoke and Ronja Oyelaran},
title = {Loud, Not Right: Validating a Smart Monitor's Cry-Classification Label Against What Actually Soothed the Baby},
year = {2026},
publisher = {Slop University},
doi = {10.5555/slop.mjo541},
url = {https://slop.university/outputs/slop-poster-validating-whether-a-mjo541/},
version = {1.0},
note = {Research poster},
}