Ha Huy Hung

About

Ha Huy Hung is a researcher at the forefront of socially-aware robotics and human-computer interaction, with a focus on bridging the gap between machine perception and natural human communication. His primary research areas include computer vision for action recognition, affective computing, and robust speech processing. Hung’s most notable contribution is the development of KFSENet, a novel key frame-based skeleton feature estimation and action recognition network that integrates face and emotion recognition. This work, which has garnered 14 citations, directly addresses the challenge of enabling social robots to engage in more personalized and intuitive interactions by simultaneously interpreting a user’s actions and emotional state. In parallel, Hung has tackled the critical issue of accessibility in speech technology. His 2023 work on improving speech recognition accuracy for non-native English speakers, using a Bag-of-Words model and deep neural networks, offers a practical solution to reduce bias in cloud-based speech-to-text services. By focusing on real-world deployment challenges, Hung’s research is paving the way for more inclusive and perceptive robotic systems that can understand and respond to diverse human users.

Research Focus

Key Achievements

Top Papers

1. 1
   KFSENet: A Key Frame-Based Skeleton Feature Estimation and Action Recognition Network for Improved Robot Vision with Face and Emotion Recognition

   14 citations · 2022
2. 2
   Improving the Accuracy of Speech Recognition Models for Non-Native English Speakers using Bag-of-Words and Deep Neural Networks

   4 citations · 2023

Key Collaborators

Contact & Links