Papers
1
Total Citations
7
H-Index
1
About
Sung Jun An is a researcher in auditory perception and human-robot interaction, with a primary focus on speech processing for humanoid platforms. His most-cited work, "Zero-crossing-based speech segregation and recognition for humanoid robots" (2009, 7 citations), addresses a critical challenge in robotic audition: enabling robots to isolate and understand speech in noisy, real-world environments. An’s key contribution lies in developing a computationally efficient method that leverages zero-crossing features—a lightweight signal processing technique—to separate target speech from background interference, making it suitable for the limited processing power of humanoid robots. This approach directly supports the goal of creating robots that can interact with humans through natural, robust auditory channels, mimicking human-like hearing capabilities. While his citation count reflects a focused niche, An’s work is notable for its practical application in humanoid robotics, bridging the gap between algorithmic speech segregation and real-time robotic performance. His research underscores the importance of designing auditory systems that are not only accurate but also computationally feasible for embodied agents, contributing to the broader field of socially interactive robots.
Research Focus
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Top Papers
- 1