6 citations · 8 across the 6 of their papers we have counts for
6 papers
Mood as a Contextual Cue for Improved Emotion Inference
Soujanya Narayana, Ibrahim Radwan, Ramanathan Subramanian +1
Psychological studies observe that emotions are rarely expressed in isolation and are typically influenced by the surrounding context. While recent studies effectively harness uni-…
A Weakly Supervised Approach to Emotion-change Prediction and Improved Mood Inference
Soujanya Narayana, Ibrahim Radwan, Ravikiran Parameshwara +4
Whilst a majority of affective computing research focuses on inferring emotions, examining mood or understanding the \textit{mood-emotion interplay} has received significantly less…
Focus on Change: Mood Prediction by Learning Emotion Changes via Spatio-Temporal Attention
Soujanya Narayana, Ramanathan Subramanian, Ibrahim Radwan +1
While emotion and mood interchangeably used, they differ in terms of duration, intensity and attributes. Even as multiple psychology studies examine the mood-emotion relationship,…
To Improve Is to Change: Towards Improving Mood Prediction by Learning Changes in Emotion
Soujanya Narayana, Ramanathan Subramanian, Ibrahim Radwan +1
Although the terms mood and emotion are closely related and often used interchangeably, they are distinguished based on their duration, intensity and attribution. To date, hardly a…
Affective Computational Advertising Based on Perceptual Metrics
Soujanya Narayana, Shweta Jain, Harish Katti +2
We present \textbf{ACAD}, an \textbf{a}ffective \textbf{c}omputational \textbf{ad}vertising framework expressly derived from perceptual metrics. Different from advertising methods…
Automated Parkinson's Disease Detection and Affective Analysis from Emotional EEG Signals
Ravikiran Parameshwara, Soujanya Narayana, Murugappan Murugappan +3
While Parkinson's disease (PD) is typically characterized by motor disorder, there is evidence of diminished emotion perception in PD patients. This study examines the utility of a…