Research
My research focuses on natural language processing and artificial
intelligence with a particular interest in the field of machine
learning (including deep learning and deep reinforcement learning)
for natural language dialogue processing (including
spoken, written, and multimodal dialogue).
The underlying concept behind my research work is how to learn
human behavior patterns from existing human-human and human-machine
interaction data in order to make natural language dialogue
systems more human-like, robust to errors and misunderstandings,
and adaptive to different types of human users and domains.
My research interests include all aspects of natural language
dialogue processing with a focus on statistical dialogue management
(deep reinforcement learning of dialogue policies),
expressive conversational speech synthesis, and speech recognition.
I also work on multi-agent modeling and intelligent tutoring
systems.