Papers
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About
Joonyeob Kim is a researcher whose work sits at the intersection of human-robot interaction and speech synthesis, with a particular focus on making robotic communication more natural and engaging. His key research areas include voice mapping for storytelling robots, text-to-speech (TTS) adaptation, and the automation of expressive vocal delivery in humanoid systems. Kim’s most cited paper, “Speaker-TTS voice mapping towards natural and characteristic robot storytelling” (2013), addresses a critical challenge in robotics: the high cost and inflexibility of using human-recorded voices for storytelling. He proposed a method to map speaker characteristics onto TTS output, enabling robots to deliver more natural, character-driven narratives without extensive manual recording. This work has garnered 2 citations, reflecting its niche but foundational role in the field. Kim’s contributions are particularly notable for their practical implications in entertainment, education, and rehabilitation, where engaging robot storytellers can enhance user experience. His research stands out for bridging the gap between robotic automation and the nuanced demands of human-like vocal expression, offering a scalable solution for more lifelike human-robot interaction.
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Top Papers
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