50 citations · 59 across the 7 of their papers we have counts for
7 papers · 1 filter
Accounting for Variations in Speech Emotion Recognition with Nonparametric Hierarchical Neural Network
Lance Ying, Amrit Romana, Emily Mower Provost
In recent years, deep-learning-based speech emotion recognition models have outperformed classical machine learning models. Previously, neural network designs, such as Multitask Le…
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…
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…
Improving Cross-Corpus Speech Emotion Recognition with Adversarial Discriminative Domain Generalization (ADDoG)
John Gideon, Melvin G McInnis, Emily Mower Provost
Automatic speech emotion recognition provides computers with critical context to enable user understanding. While methods trained and tested within the same dataset have been shown…