Papers
1
Total Citations
3
H-Index
1
About
Manisha S is a researcher at the forefront of affective computing, specializing in multimodal emotion recognition and human-computer interaction. Her work focuses on developing machine learning frameworks that interpret human emotional states from multiple data streams, particularly through bimodal approaches that combine facial expressions and vocal cues. Her most cited paper, "Bimodal Emotion Recognition using Machine Learning" (2021, 3 citations), addresses a critical challenge in creating more natural human-robot and human-computer interactions by enabling systems to decode the emotional subtext embedded in communication. This research has implications for enhancing assistive technologies, adaptive user interfaces, and empathetic AI systems. By demonstrating how machine learning can fuse different emotional signals, Manisha contributes to making technology more responsive to human affective states. Her work sits at the intersection of computer vision, speech processing, and affective science, offering practical pathways for building emotionally intelligent machines that can better understand and respond to their human users.
Research Focus
Key Achievements
Top Papers
- 1Bimodal Emotion Recognition using Machine Learning3 citations · 2021