50 citations · 60 across the 8 of their papers we have counts for
7 papers · 1 filter
Privacy Enhanced Multimodal Neural Representations for Emotion Recognition
Mimansa Jaiswal, Emily Mower Provost
Many mobile applications and virtual conversational agents now aim to recognize and adapt to emotions. To enable this, data are transmitted from users' devices and stored on centra…
When to Intervene: Detecting Abnormal Mood using Everyday Smartphone Conversations
John Gideon, Katie Matton, Steve Anderau +2
Bipolar disorder (BPD) is a chronic mental illness characterized by extreme mood and energy changes from mania to depression. These changes drive behaviors that often lead to devas…
The Ambiguous World of Emotion Representation
Vidhyasaharan Sethu, Emily Mower Provost, Julien Epps +3
Artificial intelligence and machine learning systems have demonstrated huge improvements and human-level parity in a range of activities, including speech recognition, face recogni…
Controlling for Confounders in Multimodal Emotion Classification via Adversarial Learning
Mimansa Jaiswal, Zakaria Aldeneh, Emily Mower Provost
Various psychological factors affect how individuals express emotions. Yet, when we collect data intended for use in building emotion recognition systems, we often try to do so by…
Jointly Aligning and Predicting Continuous Emotion Annotations
Soheil Khorram, Melvin G McInnis, Emily Mower Provost
Time-continuous dimensional descriptions of emotions (e.g., arousal, valence) allow researchers to characterize short-time changes and to capture long-term trends in emotion expres…
MuSE-ing on the Impact of Utterance Ordering On Crowdsourced Emotion Annotations
Mimansa Jaiswal, Zakaria Aldeneh, Cristian-Paul Bara +4
Emotion recognition algorithms rely on data annotated with high quality labels. However, emotion expression and perception are inherently subjective. There is generally not a singl…