Tetsuya Takiguchi
Papers
7
Total Citations
41
H-Index
4
About
Tetsuya Takiguchi’s research bridges the gap between humans and machines, focusing on speech interfaces, social robotics, and computer vision. His pioneering work on system request utterance detection—using acoustic and linguistic features to distinguish commands from casual conversation—has been foundational for hands-free, natural human-robot interaction. By employing techniques like multi-resolution Gabor wavelet features, he enabled robots to understand when they are being addressed, a critical step toward truly autonomous assistants. In computer vision, Takiguchi advanced generic object recognition through Conditional Random Fields and graph structural expressions, integrating global features like Bag-of-Features to improve robotic perception. His most cited work, “Human-Robot Interface Using System Request Utterance Detection Based on Acoustic Features” (2008), has garnered 12 citations and laid the groundwork for subsequent studies. More recently, his 2024 study on social robots’ listening behaviors in adult piano practice explores how nonverbal cues can enhance motivation and performance, expanding the role of robots in education. With a career spanning speech processing, robotics, and visual recognition, Takiguchi’s contributions continue to shape intuitive, responsive machines that serve people in real-world environments.
Research Focus
Key Achievements
Top Papers
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- 4Generic object recognition by graph structural expression5 citations · 2012
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