Ui-Hyun Kim

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About

Ui-Hyun Kim is a researcher in robot audition and binaural sound processing, with a focus on enabling machines to hear and locate sound sources as effectively as humans. His key research areas include binaural sound source localization (SSL), speaker tracking, and robust auditory perception in noisy, reverberant environments. Kim’s major contributions center on improving the generalized cross-correlation with phase transform (GCC-PHAT) method to overcome challenges like multipath interference and dynamic, unknown numbers of speakers. His 2013 paper on binaural SSL and tracking for time-varying speaker counts (15 citations) advanced real-time robot audition, while his 2011 work on mitigating multipath effects (7 citations) laid groundwork for more accurate direction-of-arrival estimation. Though his citation counts are modest, Kim’s work is notable for its practical impact on low-cost, binaural robotic systems—critical for applications in human-robot interaction and assistive technology. By addressing fundamental acoustic challenges, he has helped push binaural audition toward greater reliability and real-world deployment, making his research a valuable reference for engineers and students working on auditory robotics and signal processing.