most citedLinking emotions to behaviors through deep transfer learning

4 citations · 7 across the 3 of their papers we have counts for

collaborators

5 papers

eess.AS2019

Automatic prediction of suicidal risk in military couples using multimodal interaction cues from couples conversations

Sandeep Nallan Chakravarthula, Md Nasir, Shao-Yen Tseng +6

Suicide is a major societal challenge globally, with a wide range of risk factors, from individual health, psychological and behavioral elements to socio-economic aspects. Military…

cs.CL2019

An analysis of observation length requirements for machine understanding of human behaviors from spoken language

Sandeep Nallan Chakravarthula, Brian Baucom, Shrikanth Narayanan +1

The task of quantifying human behavior by observing interaction cues is an important and useful one across a range of domains in psychological research and practice. Machine learni…

cs.LG20194 cited

Linking emotions to behaviors through deep transfer learning

Haoqi Li, Brian Baucom, Panayiotis Georgiou

Human behavior refers to the way humans act and interact. Understanding human behavior is a cornerstone of observational practice, especially in psychotherapy. An important cue of…

cs.CL20193 cited

Modeling Interpersonal Linguistic Coordination in Conversations using Word Mover's Distance

Md Nasir, Sandeep Nallan Chakravarthula, Brian Baucom +3

Linguistic coordination is a well-established phenomenon in spoken conversations and often associated with positive social behaviors and outcomes. While there have been many attemp…

cs.LG2016

Sparsely Connected and Disjointly Trained Deep Neural Networks for Low Resource Behavioral Annotation: Acoustic Classification in Couples' Therapy

Haoqi Li, Brian Baucom, Panayiotis Georgiou

Observational studies are based on accurate assessment of human state. A behavior recognition system that models interlocutors' state in real-time can significantly aid the mental…