48 citations · 70 across the 8 of their papers we have counts for
8 papers
Expanding the Role of Affective Phenomena in Multimodal Interaction Research
Leena Mathur, Maja J Matarić, Louis-Philippe Morency
In recent decades, the field of affective computing has made substantial progress in advancing the ability of AI systems to recognize and express affective phenomena, such as affec…
Difference-Masking: Choosing What to Mask in Continued Pretraining
Alex Wilf, Syeda Nahida Akter, Leena Mathur +5
The self-supervised objective of masking-and-predicting has led to promising performance gains on a variety of downstream tasks. However, while most approaches randomly mask tokens…
Towards Intercultural Affect Recognition: Audio-Visual Affect Recognition in the Wild Across Six Cultures
Leena Mathur, Ralph Adolphs, Maja J Matarić
In our multicultural world, affect-aware AI systems that support humans need the ability to perceive affect across variations in emotion expression patterns across cultures. These…
Speech Representations and Phoneme Classification for Preserving the Endangered Language of Ladin
Zane Durante, Leena Mathur, Eric Ye +3
A vast majority of the world's 7,000 spoken languages are predicted to become extinct within this century, including the endangered language of Ladin from the Italian Alps. Linguis…
Affect-Aware Deep Belief Network Representations for Multimodal Unsupervised Deception Detection
Leena Mathur, Maja J Matarić
Automated systems that detect the social behavior of deception can enhance human well-being across medical, social work, and legal domains. Labeled datasets to train supervised dec…
Modeling User Empathy Elicited by a Robot Storyteller
Leena Mathur, Micol Spitale, Hao Xi +2
Virtual and robotic agents capable of perceiving human empathy have the potential to participate in engaging and meaningful human-machine interactions that support human well-being…
Unsupervised Audio-Visual Subspace Alignment for High-Stakes Deception Detection
Leena Mathur, Maja J Matarić
Automated systems that detect deception in high-stakes situations can enhance societal well-being across medical, social work, and legal domains. Existing models for detecting high…
Introducing Representations of Facial Affect in Automated Multimodal Deception Detection
Leena Mathur, Maja J Matarić
Automated deception detection systems can enhance health, justice, and security in society by helping humans detect deceivers in high-stakes situations across medical and legal dom…