9 citations · 18 across the 8 of their papers we have counts for
8 papers
Exploring Context, Attention and Audio Features for Audio Visual Scene-Aware Dialog
Shachi H Kumar, Eda Okur, Saurav Sahay +2
We are witnessing a confluence of vision, speech and dialog system technologies that are enabling the IVAs to learn audio-visual groundings of utterances and have conversations wit…
Leveraging Topics and Audio Features with Multimodal Attention for Audio Visual Scene-Aware Dialog
Shachi H Kumar, Eda Okur, Saurav Sahay +2
With the recent advancements in Artificial Intelligence (AI), Intelligent Virtual Assistants (IVA) such as Alexa, Google Home, etc., have become a ubiquitous part of many homes. Cu…
Modeling Intent, Dialog Policies and Response Adaptation for Goal-Oriented Interactions
Saurav Sahay, Shachi H Kumar, Eda Okur +2
Building a machine learning driven spoken dialog system for goal-oriented interactions involves careful design of intents and data collection along with development of intent recog…
Unobtrusive and Multimodal Approach for Behavioral Engagement Detection of Students
Nese Alyuz, Eda Okur, Utku Genc +3
We propose a multimodal approach for detection of students' behavioral engagement states (i.e., On-Task vs. Off-Task), based on three unobtrusive modalities: Appearance, Context-Pe…
Detecting Behavioral Engagement of Students in the Wild Based on Contextual and Visual Data
Eda Okur, Nese Alyuz, Sinem Aslan +3
To investigate the detection of students' behavioral engagement (On-Task vs. Off-Task), we propose a two-phase approach in this study. In Phase 1, contextual logs (URLs) are utiliz…
The Importance of Socio-Cultural Differences for Annotating and Detecting the Affective States of Students
Eda Okur, Sinem Aslan, Nese Alyuz +2
The development of real-time affect detection models often depends upon obtaining annotated data for supervised learning by employing human experts to label the student data. One o…