Sukrit Wongariyakavee
Papers
1
Total Citations
2
H-Index
1
About
Sukrit Wongariyakavee is a researcher focused on the intersection of natural language processing and human-robot interaction, with a particular emphasis on sentiment analysis for conversational agents. Their most cited work, "Sentiment Analysis for Open Domain Conversational Agent" (2021), investigates the applicability of common sentiment analysis models to open-domain human-robot interaction. Using a dataset specific to user interactions with the Alana system—an Alexa Prize socialbot—Wongariyakavee evaluates which models are most appropriate for real-time sentiment detection in dynamic, unscripted conversations. This contribution is critical for enhancing the emotional intelligence of conversational agents, enabling them to better understand and respond to user sentiment in open-domain settings. While their citation count is still growing, this work lays important groundwork for improving user experience in social robotics and dialogue systems. Wongariyakavee’s research is particularly relevant for students and researchers interested in building more empathetic, context-aware AI systems that can engage naturally with humans.
Research Focus
Key Achievements
Top Papers
- 1Sentiment Analysis for Open Domain Conversational Agent2 citations · 2021