most citedConversational Intent Understanding for Passengers in Autonomous Vehicles

2 citations · 2 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CL2019

Natural Language Interactions in Autonomous Vehicles: Intent Detection and Slot Filling from Passenger Utterances

Eda Okur, Shachi H Kumar, Saurav Sahay +2

Understanding passenger intents and extracting relevant slots are important building blocks towards developing contextual dialogue systems for natural interactions in autonomous ve…

cs.HC2019

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…

cs.CY2019

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…

cs.HC2019

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…

cs.CL20182 cited

Conversational Intent Understanding for Passengers in Autonomous Vehicles

Eda Okur, Shachi H Kumar, Saurav Sahay +2

Understanding passenger intents and extracting relevant slots are important building blocks towards developing a contextual dialogue system responsible for handling certain vehicle…