Je Hun Jeon

Je Hun Jeon
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Main area of research
Natural language & AI

Je Hun Jeon received the B.S and M.S. degree in computer science and engineering from Sogang University in Korea. During master's program he developed an interest in pronunciation modeling for an automatic speech recognition system.  After graduation, he had worked at Computer Division in Samsung Electronics as a program manager for developing new products for five years. In December 2011, he received the Ph.D. degree in computer science at The University of Texas at Dallas. His research interests include spoken/natural language processing and understanding, machine learning, and affective computing. In his free time, Je Hun enjoys traveling and spending time with his family and friends.

Selected articles

N-Best Rescoring Based on Pitch-accent Patterns

In this paper, we adopt an n-best rescoring scheme using pitch-accent patterns to improve automatic speech recognition (ASR) performance. The pitch-accent model is decoupled from

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Semi-supervised Learning for Automatic Prosodic Event Detection Using Co-training Algorithm

Most of previous approaches to automatic prosodic event detection are based on supervised learning, relying on the availability of a corpus that is annotated with

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Automatic prosodic event detection using a novel labeling and selection method in co-training

Most previous approaches to automatic prosodic event detection are based on supervised learning, relying on the availability of a corpus that is annotated with the

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Level of interest sensing in spoken dialog using decision-level fusion of acoustic and lexical evidence

Automatic detection of a user’s interest in spoken dialog plays an important role in many applications, such as tutoring systems and customer service systems. In

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